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In: Proceeding of Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS), pp 19–25. https:\u002F\u002Fdoi.org\u002F10.1109\u002FUPINLBS.2014.7033706\nBrown R, Hwang P (1997) Introduction to random signals and applied Kalman filtering: with MATLAB exercises and solutions. Wiley, New York\nBruggemann S, Greer D, Walker R (2006) Chip scale atomic clocks: Benefits to airborne GNSS navigation performance. In: Proceedings of international global navigation satellite systems society symposium, Holiday Inn, Surfers Paradise, Australia, 17–21 July 2006, pp 1–16\nCorazza G, Pedone R (2007) Generalized and average likelihood ratio testing for post detection integration. IEEE Trans Commun 55(11):2159–2171. https:\u002F\u002Fdoi.org\u002F10.1109\u002FTCOMM.2007.908531\nElders H, Dettmar U (2004) Efficient differentially coherent code\u002FDoppler acquisition of weak GPS signals. In: IEEE Proceedings of International Symposium on Spread Spectrum Techniques and Applications, pp 731–735. https:\u002F\u002Fdoi.org\u002F10.1109\u002FISSSTA.2004.1371796\nFalletti E, Pini M, Presti L (2011) Low complexity carrier-to-noise ratio estimators for GNSS digital receivers. IEEE Trans Aerosp Electron Syst 47(1):420–437. https:\u002F\u002Fdoi.org\u002F10.1109\u002FTAES.2011.5705684\nGaggero P, Borio D (2008) Ultra-stable oscillators: limits of GNSS coherent integration. In: Proceedings of ION GNSS 2008, Institute of Navigation, Savannah International Convention Center, Savannah, 16–19 September 2009 pp 565–575\nGómez D, López J, Seco G (2016) Generalized integration techniques for high-sensitivity GNSS receivers affected by oscillator phase noise. In: Proceedings of IEEE Statistical Signal Processing Workshop (SSP). Palma de Mallorca, pp 1–5. https:\u002F\u002Fdoi.org\u002F10.1109\u002FSSP.2016.7551809\nGómez D, López J, Seco G (2017) Optimal fractional non-coherent detector for high-sensitivity GNSS receivers robust against residual frequency offset and unknown bits. In: Proceedings of IEEE Workshop on Positioning, Navigation and Communications (WPNC). Bremen, pp 1–5. https:\u002F\u002Fdoi.org\u002F10.1109\u002FWPNC.2017.8250055\nGroves P (2005) GPS Signal-to-noise measurement in weak signal and high-interference environments. Navigation 52(2):83–94\nKaplan E, Hegarty C (2005) Understanding GPS: principles and applications. Artech House, Norwood\nKlobuchar J (1996) Global positioning system: theory and applications. American Institute of Aeronautics and Astronautics. Inc., Washington DC\nLopez J, Vicario J, Seco G (2008) Optimal noncoherent detector for HS-GNSS receivers. In: Proceedings of IEEE Signal Processing for Space Communications. Rhodes Island, pp 1–6. https:\u002F\u002Fdoi.org\u002F10.1109\u002FSPSC.2008.4686722\nLópez G, Seco G (2005) CN0 estimation and near-far mitigation for GNSS indoor receivers. In: Proceedings of IEEE Vehicular Technology Conference. Stockholm, pp 2624–2628. https:\u002F\u002Fdoi.org\u002F10.1109\u002FVETECS.2005.1543810\nMusumeci L, Dovis F, Silva P, Lopes H, Silva J (2014) Design of a very high sensitivity acquisition system for a space GNSS receiver. In: Proceedings of IEEE\u002FION PLANS. Hyatt Regency Hotel, Monterey, 5–8 May 2014, pp 556–568. https:\u002F\u002Fdoi.org\u002F10.1109\u002FPLANS.2014.6851417\nSchmid A, Neubauer A (2005a) Carrier to noise power estimation for enhanced sensitivity Galileo\u002FGPS receivers. In: Proceedings of IEEE Vehicular Technology Conference, vol 4. Stockholm, pp 2629–2633. https:\u002F\u002Fdoi.org\u002F10.1109\u002FVETECS.2005.1543811\nSchmid A, Neubauer A (2005b) Differential correlation for Galileo\u002FGPS receivers. In: Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing. Philadelphia, pp 953–956. https:\u002F\u002Fdoi.org\u002F10.1109\u002FICASSP.2005.1415869\nSeco G, Lopez J, Jimenez D, Lopez G (2012) Challenges in indoor global navigation satellite systems: unveiling its core features in signal processing. IEEE Signal Process Mag 29(2):108–131. https:\u002F\u002Fdoi.org\u002F10.1109\u002FMSP.2011.943410\nSträssle C, Megnet D, Mathis H, Bürgi C (2007) The squaring-loss paradox. In: Proceedings of ION GNSS 2007, Institute of Navigation, Fort Worth Convention Center, Fort Worth, 25–28 September 2007, pp 2715–2722",{"EN":119},"We address the problem of estimating the carrier-to-noise ratio (C\u002FN0) in weak signal conditions. There are several environments, such as forested areas, indoor buildings and urban canyons, where high-sensitivity global navigation satellite system (HS-GNSS) receivers are expected to work under these reception conditions. The acquisition of weak signals from the satellites requires the use of post-detection integration (PDI) techniques to accumulate enough energy to detect them. However, due to the attenuation suffered by these signals, estimating their C\u002FN0 becomes a challenge. Measurements of C\u002FN0 are important in many applications of HS-GNSS receivers such as the determination of a detection threshold or the mitigation of near-far problems. For this reason, different techniques have been proposed in the literature to estimate the C\u002FN0, but they only work properly in the high C\u002FN0 region where the coherent integration is enough to acquire the satellites. We derive four C\u002FN0 estimators that are specially designed for HS-GNSS snapshot receivers and only use the output of a PDI technique to perform the estimation. We consider four PDI techniques, namely non-coherent PDI, non-quadratic non-coherent PDI, differential PDI and truncated generalized PDI and we obtain the corresponding C\u002FN0 estimator for each of them. Our performance analysis shows a significant advantage of the proposed estimators with respect to other C\u002FN0 estimators available in the literature in terms of estimation accuracy and computational resources.",{"EN":121},"C\u002FN0 estimators for high-sensitivity snapshot GNSS receivers",{"VOID":123},"10.1007\u002Fs10291-018-0786-y","PUBLICATION","VERIFIED","Auto Verify","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10291-018-0786-y",[129,146,158],{"id":130,"sortIndex":100,"researcher":20,"roles":131,"affiliations":133,"properties":143},"fcb81bee-5b01-4564-b181-6bd776a988db",[132],"AUTHOR",[134],{"id":20,"sortIndex":21,"affiliation":135,"properties":20},{"id":136,"createTime":137,"updateTime":137,"relativeEntities":138,"slug":139,"properties":140,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"948b91d9-6906-48d8-a483-d3ffffabff8a","2024-04-16T21:10:16.767+00:00",[],"IEEC-CERES-Universitat-Autonoma-de-Barcelona-UAB-Barcelona-Spain",{"title":141},{"EN":142},"IEEC-CERES, Universitat Autonoma de Barcelona (UAB), Barcelona, Spain",{"title":144},{"VI":145},"José A. López-Salcedo",{"id":147,"sortIndex":21,"researcher":20,"roles":148,"affiliations":149,"properties":155},"b5cb5de5-e483-4e1d-ac78-5e68828a2088",[132],[150],{"id":20,"sortIndex":21,"affiliation":151,"properties":20},{"id":136,"createTime":137,"updateTime":137,"relativeEntities":152,"slug":139,"properties":153,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":154},{"EN":142},{"title":156},{"VI":157},"David Gómez-Casco",{"id":159,"sortIndex":99,"researcher":20,"roles":160,"affiliations":161,"properties":167},"f01e0db4-2f85-4bb5-8233-90ff0624e4d3",[132],[162],{"id":20,"sortIndex":21,"affiliation":163,"properties":20},{"id":136,"createTime":137,"updateTime":137,"relativeEntities":164,"slug":139,"properties":165,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":166},{"EN":142},{"title":168},{"VI":169},"Gonzalo Seco-Granados","ARTICLE",{"url":127,"publisher":172,"properties":200},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":173,"slug":10,"properties":174,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":178,"manageAffiliations":179,"indexDatabases":180,"url":94,"thumbnailPath":20,"statistic":195,"gsStatistic":20,"type":104,"analyzePriority":20},[],{"issn":175,"eissn":176,"title":177},{"VOID":13},{"VOID":15},{"EN":17},[],[],[181,188],{"id":57,"indexDatabase":182,"url":72,"indexYears":20,"academicFieldIds":187,"indexDatabaseRanking":20},{"id":59,"createTime":60,"updateTime":61,"relativeEntities":183,"label":184,"description":185,"key":68,"publicationTags":186,"standard":20},[],{"EN":64,"VI":64},{"VI":66,"EN":67},[70,71],[74],{"id":76,"indexDatabase":189,"url":89,"indexYears":90,"academicFieldIds":194,"indexDatabaseRanking":93},{"id":78,"createTime":79,"updateTime":80,"relativeEntities":190,"label":191,"description":192,"key":86,"publicationTags":193,"standard":20},[],{"EN":83,"VI":83},{"EN":83,"VI":85},[88],[92],{"impactFactor":21,"impactFactorByYear":196,"i10Index":21,"i10IndexLast5Year":21,"totalPublication":97,"totalPublicationByYear":197,"totalCitation":21,"totalCitationByYear":198,"totalCitationPerPublication":21,"totalCitationPerPublicationByYear":199,"hindexLast5Year":21,"hindex":21},{},{"1995":99,"1998":100,"1999":99,"2001":100,"2002":100,"2003":100,"2004":100,"2011":100,"2013":100,"2017":100,"2018":99,"2020":100,"2021":99,"2022":101},{},{},{"volume":201,"pages":203},{"VOID":202},"22",{"VOID":204},"1-11","2018-09-19",2018,false,{"id":209,"createTime":210,"updateTime":211,"relativeEntities":212,"slug":213,"properties":214,"entityType":124,"verifyStatus":125,"verifyTime":211,"verifyNote":126,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":223,"fullTextUrl":20,"authors":224,"publicationType":170,"publisherRelationship":264,"citationCount":20,"citationInfo":20,"publishDate":298,"publishYear":299,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":20,"openAccess":20,"references":20,"isForceReanalyzing":207},"7436d3ff-bcd4-47fc-acc4-c5156eb16c19","2024-01-18T00:18:20.957+00:00","2025-02-12T23:56:10.052+00:00",[],"Attitude-determination-by-integration-of-MEMS-inertial-sensors-and-GPS-for-autonomous-agriculture-applications",{"references":215,"abstract":217,"title":219,"doi":221},{"VOID":216},"Bar-Itzhack IY (1977) Navigation computation in terrestrial strapdown inertial navigation system. IEEE Trans on AES 13(6):679–689\nBekkeng JK (2009) Calibration of a novel MEMS inertial reference unit. IEEE Trans Instrum Measure 58(6):1967–1974\nCohen CE (1996) Attitude determination. Global positioning system, theory and applications, vol. II. In: Parkinson BW, Spilker JJ (eds) Progress in astronautics and aeronautics, vol. 164, AIAA, Washington DC, pp 519–538\nCole A (2008) Integrating external position information with GPS using existing GPS processing software for precision agriculture applications. In: Proceedings of ION GNSS 2008, Savannah, Georgia, September 16–19, pp 2156–2164\nCole A, Wang J, Dempster AG, Rizos C (2009) VirtuaLites: concepts and numerical test results. J Appl Geodesy 3(4):213–221\nFarrell J, Barth M (1998) The global positioning system and inertial navigation. McGraw-Hill, Chap. 6.4, pp 187–242\nFourati H, Manamanni N, Afilal L, Handrich Y (2009) Rigid body motions estimation using inertial sensors: bio-logging application. In: 7th IFAC symposium on modelling and control in biomedical systems (including biological systems), Alborg, Denmark, August 12–14\nGeng Y, Cole A, Dempster AG, Rizos C, Wang J (2007) Developing a low-cost MEMS IMU\u002FDGPS integrated system for robust machine automation. In: Proceedings of ION-GNSS 2007, Fort Worth, Texas, September 25–28, pp 1618–1624\nGodha S, Cannon ME (2007) GPS\u002FMEMS INS integrated system for navigation in urban areas. GPS Solutions 11(3):193–203\nGriepentrog HW, Nørremark M, Nielsen J (2006) Autonomous intra-row rotor weeding based on GPS. In: Proceedings of CIGR world congress agricultural engineering for a better world, Bonn, Germany, September 3–7, CD ROM proceedings\nKellar W, Roberts P, Zelzer O (2008) A self calibrating attitude determination system for precision farming using multiple low-cost complementary sensors In: 1st International conference on machine control & guidance, Zurich, Switzerland, June 24–26\nLi Y, Murata M, Sun B (2002) New approach to attitude determination using global positioning system carrier phase measurements. J Guid Control Dyn 25(1):130–136\nLi Y, Dempster AG, Li B, Wang J, Rizos C (2006) A low-cost attitude heading reference system by combination of GPS and magnetometers and MEMS inertial sensors for mobile applications. J Global Position Syst 5(1–2):88–95\nLi Y, Dusha D, Kellar W, Dempster AG (2009a) Calibrated MEMS inertial sensors with GPS for a precise attitude heading reference system on autonomous farming tractors. In: Proceedings of ION-GNSS2009, Savannah, Georgia, September 22–25, pp 2138–2145\nLi Y, Efatmaneshnik M, Cole A, Dempster AG (2009b) Performance evaluation of AHRS Kalman Filter for MojoRTK System. In: Proceedings of IGNSS symposium 2009, international global navigation satellite systems society, Surfers Paradise, Australia, December 1–3, CD-ROM procs\nReid JF, Zhang Q, Noguchi N, Dickson M (2000) Agricultural automatic guidance research in North America. Comput Electron Agric 25(1–2):155167\nRetscher G (2007) Test and integration of location sensors for a multi-sensor personal navigator. J Navigation 60(1):107–117\nRios JA, White E (2001) Fusion filter algorithm enhancements for a MEMS GPS\u002FIMU. In: Proceedings of ION-GNSS 2001, Salt Lake City, Utah, September 11–14, pp 1382–1393\nRizos C, Han S (2003) Reference station network based RTK systems—concepts & progress, Wuhan University. J Nature Sci 8(2B):566–574\nRoberts JM, Corke PI, Buskey G (2002) Low-cost flight control system for a small autonomous helicopter. In: Proceedings of 2002 Australian conference on robotics and automation, Auckland, New Zealand, November 27–29, pp 71–76\nSheh RK, Milstein AH, McGill M, Salleh R, Hengst B, Sammut C (2009) Semi-autonomous Robots for RoboCupRescue. In: Proceedings of 2009 Australasian conference on robotics and automation (ACRA), Sydney, Australia, December 2–4\nStafford JV (2000) Implementing precision agriculture in the 21st century. J Agric Eng Res 76:267–270\nSupej M (2010) 3D measurements of alpine skiing with an inertial sensor motion capture suit and GNSS RTK system. J Sports Sci 28(7):759–769\nTillett ND (1991) Automatic guidance sensors for agricultural field machines: a review. J Agric Eng Res 50(33):167–187\nWu Y, Wang T, Liang J, Wang C, Zhang C (2008) Attitude determination for small helicopter using extended kalman filter. IEEE Xplore 2008:577–581",{"EN":218},"Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) technologies, which has widespread usage in industry, is also regarded as an ideal solution for automated agriculture because it fulfils the accuracy, reliability and availability requirements of industrial and agricultural applications. Agriculture applications use position, velocity and heading information for automated vehicle guidance and control to enhance the yield and quality of the crop, and in order to vary the application of fertilizer and herbicides according to soil heterogeneity at sub-field level. A loosely coupled GPS\u002FINS integration algorithm known as “AhrsKf” is introduced for automated agriculture vehicle guidance and control utilizing MEMS inertial sensors and GPS. The AhrsKf can produce high-frequency attitude solutions for the vehicle’s guidance and control system, by using inputs from a single survey grade L1\u002FL2 antenna, eliminating the need for the previous two antenna solutions. Given its agricultural application, the AhrsKf has been implemented with some specific design features to improve the accuracy of the attitude solution including, temperature compensation of the inertial sensors, and the aid of plough lines of farm lands. To evaluate the AhrsKf solution, two benchmarking tests have been conducted by using a three-antenna GPS system and NovAtel’s SPAN-CPT. The results have demonstrated that the AhrsKf solution is stable and can correctly track the movement of the farming vehicle.",{"EN":220},"Attitude determination by integration of MEMS inertial sensors and GPS for autonomous agriculture applications",{"VOID":222},"10.1007\u002Fs10291-011-0207-y","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10291-011-0207-y",[225,240,252],{"id":226,"sortIndex":21,"researcher":20,"roles":227,"affiliations":228,"properties":237},"d24545e4-693a-4241-a731-3660d3e0c423",[132],[229],{"id":20,"sortIndex":21,"affiliation":230,"properties":20},{"id":231,"createTime":232,"updateTime":232,"relativeEntities":233,"slug":20,"properties":234,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"76d20304-b814-4020-9065-0f7457757cbb","2023-12-20T20:44:01.861+00:00",[],{"title":235},{"VI":236},"School of Surveying & Spatial Information Systems, University of New South Wales, Sydney, Australia",{"title":238},{"VI":239},"Yong Li",{"id":241,"sortIndex":100,"researcher":20,"roles":242,"affiliations":243,"properties":249},"92df8449-5185-48de-90cb-a4e4fe885daa",[132],[244],{"id":20,"sortIndex":21,"affiliation":245,"properties":20},{"id":231,"createTime":232,"updateTime":232,"relativeEntities":246,"slug":20,"properties":247,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":248},{"VI":236},{"title":250},{"VI":251},"Mahmoud Efatmaneshnik",{"id":253,"sortIndex":99,"researcher":20,"roles":254,"affiliations":255,"properties":261},"884a0c9d-2ac2-4869-afce-0a1da8a6d54b",[132],[256],{"id":20,"sortIndex":21,"affiliation":257,"properties":20},{"id":231,"createTime":232,"updateTime":232,"relativeEntities":258,"slug":20,"properties":259,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":260},{"VI":236},{"title":262},{"VI":263},"Andrew G. 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J, Tang Y, Wu X, Cao J, Ma M (2012) Evaluation of ionospheric correction models in the middle latitude. 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GPS Solut 26(2):52\nHahn JH, Powers ED (2005) Implementation of the GPS to Galileo time offset (GGTO),In: Proceedings of 2005 joint IEEE international frequency control symposium and precise time & time interval (PPTI) Systems & applications meeting, Vancouver, pp 33–37\nHauschild A, Steigenberger P, Montenbruck O (2019) Inter-receiver GNSS pseudorange biases and their effect on clock and DCB estimation. In: Proceedings ION GNSS+ 2019, Institute of Navigation, Miami, Florida, pp 3675–3685\nHauschild A, Montenbruck O (2016) A study on the dependency of GNSS pseudorange biases on correlator spacing. GPS Solut 20(2):159–171\nHegarty C, Powers E, Foville B (2004) Accounting for timing biases between GPS, modernized GPS, and Galileo signals. In: Proceedings of 36th annual precise time and time interval meeting, Washington DC, pp 307–317\nKouba J (2009) A guide to using international GNSS service (IGS) products. http:\u002F\u002Facc.igs.org\u002FUsingIGSProductsVer21.pdf\nLi M, Yuan Y (2021) Estimation and analysis of the observable-specific code biases estimated using multi-GNSS observations and global ionospheric maps. Remote Sens 13(16):3096\nLi X, Zhang X, Ge M (2011) Regional reference network augmented precise point positioning for instantaneous ambiguity resolution. J Geod 85:151–158\nLi X, Ge M, Dai X, Ren X, Fritsche M, Wickert J, Schuh H (2015) Accuracy and reliability of multi-GNSS real-time precise positioning: GPS, GLONASS, BeiDou, and Galileo. J Geod 89(6):607–635\nLi R, Li Z, Wang N, Tang C, Ma H, Zhang Y, Wang Z, Wu J (2021) Considering inter-receiver pseudorange biases for BDS-2 precise orbit determination. Measurement 177:109251\nLiu X, Jiang W, Chen H, Zhao W, Huo L, Huang L, Chen Q (2019) An analysis of inter-system biases in BDS\u002FGPS precise point positioning. GPS Solut 23:116\nMi X, Zhang B, Odolinski R, Yuan Y (2020) On the temperature sensitivity of multi-GNSS intra- and inter-system biases and the impact on RTK positioning. GPS Solut 24(4):112. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-020-01027-5\nMontenbruck O, Hauschild A, Hessels U (2011) Characterization of GPS\u002FGIOVE sensor stations in the CONGO network. GPS Solut 15:193–205. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-010-0182-8\nMontenbruck O, Hauschild A, Steigenberger P (2014) Differential code bias estimation using multi-GNSS observations and global ionosphere maps. Navigation 61(3):191–201\nMontenbruck O, Steigenberger P, Prange L, Deng Z, Zhao Q, Perosanz F et al (2017) The multi-GNSS experiment (MGEX) of the international GNSS service (IGS)-achievements, prospects and challenges. Adv Space Res 59(7):1671–1697\nOdijk D, Teunissen PJG (2013) Characterization of between-receiver GPS-Galileo inter-system biases and their effect on mixed ambiguity resolution. GPS Solut 17(4):521–533. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-012-0298-0\nOdijk D, Zhang B, Khodabandeh A, Odolinski R, Teunissen PJG (2016) On the estimability of parameters in undifferenced, uncombined GNSS network and PPP-RTK user models by means of S-system theory. J Geodesy 90(1):15–44. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00190-015-0854-9\nOdolinski R, Teunissen PJG, Odijk D (2015) Combined BDS, Galileo, QZSS and GPS single-frequency RTK. GPS Solut 19(1):151–163. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-014-0376-6\nPaziewski J, Wielgosz P (2015) Accounting for Galileo-GPS inter-system biases in precise satellite positioning. J Geod 89:81–93. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00190-014-0763-3\nRebischung P, Schmid R (2016) IGS14\u002Figs14.atx: a new framework for the IGS products. In: American geophysical union fall meeting 2016, San Francisco\nSchaer S, Gurtner W, Feltens J (1998) IONEX: the ionosphere map exchange format version 1. In Proceedings of the IGS AC Workshop, Darmstadt, 9–11 Feb 1998\nShi C, Yi W, Song W, Lou Y, Yao Y, Zhang R (2013) GLONASS pseudorange inter-channel biases and their effects on combined GPS\u002FGLONASS precise point positioning. GPS Solut 17(4):439–451\nSteigenberger P, Fritsche M, Dach R, Schmid R, Montenbruck O, Uhlemann M, Prange L (2016) Estimation of satellite antenna phase center offsets for Galileo. J Geod 90(8):773–785\nWang N, Yuan Y, Li Z, Montenbruck O, Tan B (2016) Determination of differential code biases with multi-GNSS observations. J Geod 90(2):209–228\nWang N, Li Z, Duan B, Hugentobler U, Wang L (2020) GPS and GLONASS observable-specific code bias estimation: comparison of solutions from the IGS and MGEX networks. J Geodesy 94:74\nZang N, Li B, Nie L, Shen Y (2020) Inter-system and inter-frequency code biases: simultaneous estimation, daily stability and applications in multi-GNSS single-frequency precise point positioning. GPS Solut 24(1):18. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-019-0926-z\nZeng A, Yang Y, Ming F, Jing Y (2017) BDS-GPS inter-system bias of code observation and its preliminary analysis. GPS Solut 21(2):1–9\nZhang B, Teunissen PJG (2016) Zero-baseline analysis of GPS\u002FBeiDou\u002Fgalileo between-receiver differential code biases (BR-DCBs): time-wise retrieval and preliminary characterization. Navigation 63(2):118–191\nZhang B, Zhao C, Odolinski R, Liu T (2021) Functional model modification of precise point positioning considering the time varying code biases of a receiver. Satell Navig 2(1):11. https:\u002F\u002Fdoi.org\u002F10.1186\u002Fs43020-021-00040-4\nZhao Q, Guo J, Liu S, Tao J, Hu Z, Chen G (2021) A variant of raw observation approach for BDS\u002FGNSS precise point positioning with fast integer ambiguity resolution. Satell Navig 2(1):29",{"EN":573},"Inter-system bias (ISB) parameters are usually introduced in multi-GNSS processing. However, the differences in correlation processing within GNSS receivers can introduce signal distortion bias (SDB) into pseudorange observations. SDB differences of these satellites from the same constellation, similar to the GLONASS inter-frequency bias (IFB) related to individual frequencies, can cause intra-system biases. Based on multi-GNSS observations that consider intra-system bias, the relationship between intra-system and inter-system biases and their impacts on the multi-GNSS undifferenced (UD) model are analyzed in this article. Then, empirical calibration strategies are proposed. Ten receiver types from four manufacturers are selected to analyze the intra-system bias characteristics of code division multiple access (CDMA) and frequency division multiple access (FDMA), and the calibrations and improvements of the multi-GNSS solution are also analyzed. The results show that the intra-system biases of GPS and Galileo remain at the centimeter–decimeter level with 10-cm stability, while bias of BDS can reach several meters with worse stability. The intra-system biases of CDMA signals have stronger consistency among the same types of receivers than those of FDMA. One month of data verified the centimeter-level differences between ISB parameters that were independently estimated based on multi-GNSS precise products with unified datum and inter-constellation differences in intra-system biases. The pre-estimated intra-system bias can be used to calibrate pseudorange residuals and further promote the convergence speed of single or multi-GNSS precise point positioning (PPP), especially for BDS and GLONASS. Comparative experiments show that intra-system bias calibration can decrease the residual RMS of BDS by 22 cm on average and that of GLONASS by 41 cm, with 15% and 23% improvement rates, respectively. The convergence time of BDS PPP in the horizontal and vertical directions can be reduced by 10 min to half an hour with approximately 20–60% improvement rates. For GLONASS PPP, the convergence time can also be reduced by more than 40 min with a 50–90% improvement.",{"EN":575},"Characteristic analysis and calibration of CDMA and FDMA intra-system and inter-system biases in multi-GNSS precise point positioning",{"VOID":577},"10.1007\u002Fs10291-023-01536-z","https:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs10291-023-01536-z",[580,607,619,631,643,655],{"id":581,"sortIndex":21,"researcher":20,"roles":582,"affiliations":583,"properties":604},"cc5da9f5-b476-4703-bc77-00871ecdc36f",[132],[584,592],{"id":20,"sortIndex":21,"affiliation":585,"properties":20},{"id":586,"createTime":587,"updateTime":587,"relativeEntities":588,"slug":20,"properties":589,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"0ee60a72-3447-47f9-8356-d64d7fd9d7ce","2023-12-13T19:05:56.424+00:00",[],{"title":590},{"VI":591},"School of Geomatics, Liaoning Technical University, Fuxin, China",{"id":593,"sortIndex":100,"affiliation":594,"properties":603},"23d0ebbd-388b-49e2-9254-de4d6c5abc3f",{"id":595,"createTime":596,"updateTime":597,"relativeEntities":598,"slug":599,"properties":600,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"815d837b-e5b1-4c02-a140-683510e2ba63","2024-02-18T14:49:46.871+00:00","2024-09-23T17:30:46.464+00:00",[],"School-of-Electronic-and-Information-Engineering-Beihang-University-Beijing-China",{"title":601},{"VI":602},"School of Electronic and Information Engineering, Beihang University, Beijing, China",{},{"title":605},{"VI":606},"Liang Chen",{"id":608,"sortIndex":100,"researcher":20,"roles":609,"affiliations":610,"properties":616},"7256bb3e-e2ac-484f-af09-260779193d9d",[132],[611],{"id":20,"sortIndex":21,"affiliation":612,"properties":20},{"id":586,"createTime":587,"updateTime":587,"relativeEntities":613,"slug":20,"properties":614,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":615},{"VI":591},{"title":617},{"VI":618},"Zijia Wang",{"id":620,"sortIndex":101,"researcher":20,"roles":621,"affiliations":622,"properties":628},"dbfb62ee-340d-415f-b051-308a3d9d96f3",[132],[623],{"id":20,"sortIndex":21,"affiliation":624,"properties":20},{"id":336,"createTime":337,"updateTime":337,"relativeEntities":625,"slug":20,"properties":626,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":627},{"VI":341},{"title":629},{"VI":630},"Xiaopeng Gong",{"id":632,"sortIndex":424,"researcher":20,"roles":633,"affiliations":634,"properties":640},"c0036c34-3d1c-415b-b314-79abde11521a",[132],[635],{"id":20,"sortIndex":21,"affiliation":636,"properties":20},{"id":336,"createTime":337,"updateTime":337,"relativeEntities":637,"slug":20,"properties":638,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":639},{"VI":341},{"title":641},{"VI":642},"Jun Tao",{"id":644,"sortIndex":99,"researcher":20,"roles":645,"affiliations":646,"properties":652},"4d648e64-9053-4a91-9f9b-cd7fdd65a4a2",[132],[647],{"id":20,"sortIndex":21,"affiliation":648,"properties":20},{"id":595,"createTime":596,"updateTime":597,"relativeEntities":649,"slug":599,"properties":650,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":651},{"VI":602},{"title":653},{"VI":654},"Fu Zheng",{"id":656,"sortIndex":422,"researcher":20,"roles":657,"affiliations":658,"properties":664},"bdd9e7a4-a9f0-4ac7-abdc-b73d3e49f6dc",[132],[659],{"id":20,"sortIndex":21,"affiliation":660,"properties":20},{"id":595,"createTime":596,"updateTime":597,"relativeEntities":661,"slug":599,"properties":662,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":663},{"VI":602},{"title":665},{"VI":666},"Chuang Shi",{"url":578,"publisher":668,"properties":696},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":669,"slug":10,"properties":670,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":674,"manageAffiliations":675,"indexDatabases":676,"url":94,"thumbnailPath":20,"statistic":691,"gsStatistic":20,"type":104,"analyzePriority":20},[],{"issn":671,"eissn":672,"title":673},{"VOID":13},{"VOID":15},{"EN":17},[],[],[677,684],{"id":57,"indexDatabase":678,"url":72,"indexYears":20,"academicFieldIds":683,"indexDatabaseRanking":20},{"id":59,"createTime":60,"updateTime":61,"relativeEntities":679,"label":680,"description":681,"key":68,"publicationTags":682,"standard":20},[],{"EN":64,"VI":64},{"VI":66,"EN":67},[70,71],[74],{"id":76,"indexDatabase":685,"url":89,"indexYears":90,"academicFieldIds":690,"indexDatabaseRanking":93},{"id":78,"createTime":79,"updateTime":80,"relativeEntities":686,"label":687,"description":688,"key":86,"publicationTags":689,"standard":20},[],{"EN":83,"VI":83},{"EN":83,"VI":85},[88],[92],{"impactFactor":21,"impactFactorByYear":692,"i10Index":21,"i10IndexLast5Year":21,"totalPublication":97,"totalPublicationByYear":693,"totalCitation":21,"totalCitationByYear":694,"totalCitationPerPublication":21,"totalCitationPerPublicationByYear":695,"hindexLast5Year":21,"hindex":21},{},{"1995":99,"1998":100,"1999":99,"2001":100,"2002":100,"2003":100,"2004":100,"2011":100,"2013":100,"2017":100,"2018":99,"2020":100,"2021":99,"2022":101},{},{},{"volume":697,"pages":699},{"VOID":698},"27",{"VOID":700},"1-21","2023-10-04",2023,{"id":704,"createTime":705,"updateTime":706,"relativeEntities":707,"slug":708,"properties":709,"entityType":124,"verifyStatus":125,"verifyTime":706,"verifyNote":126,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":718,"fullTextUrl":20,"authors":719,"publicationType":170,"publisherRelationship":786,"citationCount":20,"citationInfo":20,"publishDate":820,"publishYear":821,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":20,"openAccess":20,"references":20,"isForceReanalyzing":207},"2665cc4d-7333-494c-85da-9f329cc5a6d6","2023-12-06T19:25:05.095+00:00","2024-12-09T23:54:33.737+00:00",[],"On-the-temperature-sensitivity-of-multi-GNSS-intra-and-inter-system-biases-and-the-impact-on-RTK-positioning",{"references":710,"abstract":712,"title":714,"doi":716},{"VOID":711},"Choi K, Yoo W, Kim L, Lee Y, Lee H (2019) A distributed method to estimate RDCB and SDCB using a GPS receiver network. Meas Sci Technol 30(10):105105. https:\u002F\u002Fdoi.org\u002F10.1088\u002F1361-6501\u002Fab25c3\nCoster A, Williams J, Weatherwax A, Rideout W, Herne D (2013) Accuracy of GPS total electron content: GPS receiver bias temperature dependence. Radio Sci 48(2):190–196. https:\u002F\u002Fdoi.org\u002F10.1002\u002Frds.20011\nDalla Torre A, Caporali A (2015) An analysis of intersystem biases for multi-GNSS positioning. GPS Solut 19(2):297–307. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-014-0388-2\nDeng C, Tang W, Liu J, Shi C (2014) Reliable single-epoch ambiguity resolution for short baselines using combined GPS\u002FBeiDou system. GPS Solut 18(3):375–386. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-013-0337-5\nElghazouly A, Doma M, Sedeek A (2019) Estimating satellite and receiver differential code bias using a relative Global Positioning System network. Ann Geophys-Germany 37(6):1039–1047. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fangeo-37-1039-2019\nGao W, Gao C, Pan S, Meng X, Xia Y (2017) Inter-system differencing between GPS and BDS for medium-baseline RTK positioning. Remote Sensing 9(9):948. https:\u002F\u002Fdoi.org\u002F10.3390\u002Frs9090948\nGao W, Meng X, Gao C, Pan S, Wang D (2018) Combined GPS and BDS for single-frequency continuous RTK positioning through real-time estimation of differential inter-system biases. GPS Solut 22(1):20. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-017-0687-5\nGioia C, Borio D (2016) A statistical characterization of the Galileo-to-GPS inter-system bias. J Geodesy 90(11):1279–1291. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00190-016-0925-6\nHåkansson M, Jensen A, Horemuz M, Hedling G (2017) Review of code and phase biases in multi-GNSS positioning. GPS Solut 21(3):849–860. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-016-0572-7\nJiang N, Xu Y, Xu T, Xu G, Sun Z, Schuh H (2017) GPS\u002FBDS short-term ISB modelling and prediction. GPS Solut 21(1):163–175. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-015-0513-x\nLi M, Yuan Y, Wang N, Liu T, Chen Y (2018) Estimation and analysis of the short-term variations of multi-GNSS receiver differential code biases using global ionosphere maps. J Geodesy 92(8):889–903. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00190-017-1101-3\nLi W, Wang G, Mi J, Zhang S (2019) Calibration errors in determining slant Total Electron Content (TEC) from multi-GNSS data. Adv Space Res 63(5):1670–1680. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.asr.2018.11.020\nMi X, Zhang B, Yuan Y (2019a) Multi-GNSS inter-system biases: estimability analysis and impact on RTK positioning. GPS Solut 23(3):81. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-019-0873-8\nMi X, Zhang B, Yuan Y (2019b) Stochastic modeling of between-receiver single-differenced ionospheric delays and its application to medium baseline RTK positioning. Meas Sci Technol 30(9):095008. https:\u002F\u002Fdoi.org\u002F10.1088\u002F1361-6501\u002Fab11b5\nMi X, Zhang B, Yuan Y, Luo X (2019c) Characteristics of GPS, BDS2, BDS3 and Galileo inter-system biases and their influence on RTK positioning. Meas Sci Technol 31(1):015009. https:\u002F\u002Fdoi.org\u002F10.1088\u002F1361-6501\u002Fab4209\nNadarajah N, Khodabandeh A, Wang K, Choudhury M, Teunissen PJG (2018) Multi-GNSS PPP-RTK: from large- to small-scale networks. Sensors 18(4):1078. https:\u002F\u002Fdoi.org\u002F10.3390\u002Fs18041078\nOdijk D, Teunissen PJG (2012) Characterization of between-receiver GPS-Galileo inter-system biases and their effect on mixed ambiguity resolution. GPS Solut 17(4):521–533. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-012-0298-0\nOdijk D, Nadarajah N, Zaminpardaz S, Teunissen PJG (2017) GPS, Galileo, QZSS and IRNSS differential ISBs: estimation and application. GPS Solut 21(2):439–450. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-016-0536-y\nOdolinski R, Teunissen PJG (2017) Low-cost, 4-system, precise GNSS positioning: a GPS, Galileo, BDS and QZSS ionosphere-weighted RTK analysis. Meas Sci Technol 28(12):125801. https:\u002F\u002Fdoi.org\u002F10.1088\u002F1361-6501\u002Faa92eb\nOdolinski R, Teunissen PJG, Odijk D (2014a) Combined BDS, Galileo, QZSS and GPS single-frequency RTK. GPS Solut 19(1):151–163. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-014-0376-6\nOdolinski R, Teunissen PJG, Odijk D (2014b) First combined COMPASS\u002FBeiDou-2 and GPS positioning results in Australia. Part II: Single- and multiple-frequency single-baseline RTK positioning. J Spatial Sci 59(1):25–46. https:\u002F\u002Fdoi.org\u002F10.1080\u002F14498596.2013.866913\nOdolinski R, Teunissen PJG, Odijk D (2015) Combined GPS + BDS for short to long baseline RTK positioning. Meas Sci Technol 26(4):045801. https:\u002F\u002Fdoi.org\u002F10.1088\u002F0957-0233\u002F26\u002F4\u002F045801\nPaziewski J, Wielgosz P (2014) Accounting for Galileo–GPS inter-system biases in precise satellite positioning. J Geodesy 89(1):81–93. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00190-014-0763-3\nPaziewski J, Sieradzki R, Wielgosz P, Technology (2015) Selected properties of GPS and Galileo-IOV receiver intersystem biases in multi-GNSS data processing. Meas Sci Technol 26(9):095008. https:\u002F\u002Fdoi.org\u002F10.1088\u002F0957-0233\u002F26\u002F9\u002F095008\nSu K, Jin S (2019) Triple-frequency carrier phase precise time and frequency transfer models for BDS-3. GPS Solut 23(3):86. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-019-0879-2\nTeunissen PJG (1995) The least-squares ambiguity decorrelation adjustment: a method for fast GPS integer ambiguity estimation. J Geodesy 70:65–82. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fbf00863419\nTeunissen PJG (2018) Distributional theory for the DIA method. J Geodesy 92(1):59–80. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00190-017-1045-7\nYang Y, Xu Y, Li J, Yang C (2018) Progress and performance evaluation of BeiDou global navigation satellite system: data analysis based on BDS-3 demonstration system. Sci China Earth Sci 61(5):614–624. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11430-017-9186-9\nZha J, Zhang B, Yuan Y, Zhang X, Li M (2019) Use of modified carrier-to-code leveling to analyze temperature dependence of multi-GNSS receiver DCB and to retrieve ionospheric TEC. GPS Solut 23(4):103. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-019-0895-2\nZhang B, Teunissen PJG (2015) Characterization of multi-GNSS between-receiver differential code biases using zero and short baselines. Sci Bull 60(21):1840–1849. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11434-015-0911-z\nZhang B, Teunissen PJG, Yuan Y (2016) On the short-term temporal variations of GNSS receiver differential phase biases. J Geodesy 91(5):563–572. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00190-016-0983-9\nZhang B, Liu T, Yuan Y (2017) GPS receiver phase biases estimable in PPP-RTK networks: dynamic characterization and impact analysis. J Geodesy 92(6):659–674. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00190-017-1085-z\nZhang X, Zhang B, Yuan Y, Zha J (2020) Extending multipath hemispherical model to account for time-varying receiver code biases. Adv Space Res 65(1):650–662. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.asr.2019.11.003",{"EN":713},"The intra-system biases, including differential code biases (DCBs) and differential phase biases (DPBs), are generally defined as the receiver-dependent hardware delays between different frequencies in a single global navigation satellite system (GNSS) constellation. Likewise, the inter-system biases (ISBs) are the differential code and phase hardware delays between different GNSSs, which are of great relevance for combined processing of multi-GNSS and multi-frequency observations. Although the two biases are usually assumed to remain unchanged for at least 1 day, they sometimes can exhibit remarkable intraday variability, likely due to environmental factors, particularly the ambient temperature. It has been proved that the possible short-term temporal variations of receiver DCBs and DPBs are directly related to ambient temperature fluctuation. We analyze whether the variability of the biases is sensitive to temperature and further identify how this affects the performance of real-time kinematic (RTK) positioning. Our numerical tests, carried out using GPS, BDS-3, Galileo and QZSS observations collected by zero and short baselines, suggest two major findings. First, we found that while ISBs associated with overlapping frequencies are fairly stable, those associated with non-overlapping frequencies can exhibit remarkable variability over a rather short period of time, driven by the changes of ambient temperature. Second, by pre-calibrating and modeling of the biases for the baselines at hand, the empirical success rates and positioning performance can be significantly improved when compared to classical and inter-system differencing, with both models assuming time-invariant receiver DCBs, DPBs and ISBs.",{"EN":715},"On the temperature sensitivity of multi-GNSS intra- and inter-system biases and the impact on RTK positioning",{"VOID":717},"10.1007\u002Fs10291-020-01027-5","https:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs10291-020-01027-5",[720,735,759,771],{"id":721,"sortIndex":100,"researcher":20,"roles":722,"affiliations":723,"properties":732},"329a8fb4-97e4-4663-87a9-993937840fc1",[132],[724],{"id":20,"sortIndex":21,"affiliation":725,"properties":20},{"id":726,"createTime":727,"updateTime":727,"relativeEntities":728,"slug":20,"properties":729,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"86dcecca-d864-4a15-9b32-e76de5049ba8","2024-02-12T03:07:34.071+00:00",[],{"title":730},{"VI":731},"State Key Laboratory of Geodesy and Earth’s Dynamics, Institute of Geodesy and Geophysics, Wuhan, China",{"title":733},{"VI":734},"Baocheng 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of Chinese Academy of Sciences, Beijing, China",{},{"title":757},{"VI":758},"Xiaolong Mi",{"id":760,"sortIndex":101,"researcher":20,"roles":761,"affiliations":762,"properties":768},"eaba49fb-8c67-49bd-8e17-e041334e07a6",[132],[763],{"id":20,"sortIndex":21,"affiliation":764,"properties":20},{"id":726,"createTime":727,"updateTime":727,"relativeEntities":765,"slug":20,"properties":766,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":767},{"VI":731},{"title":769},{"VI":770},"Yunbin 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Odolinski",{"url":718,"publisher":787,"properties":815},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":788,"slug":10,"properties":789,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":793,"manageAffiliations":794,"indexDatabases":795,"url":94,"thumbnailPath":20,"statistic":810,"gsStatistic":20,"type":104,"analyzePriority":20},[],{"issn":790,"eissn":791,"title":792},{"VOID":13},{"VOID":15},{"EN":17},[],[],[796,803],{"id":57,"indexDatabase":797,"url":72,"indexYears":20,"academicFieldIds":802,"indexDatabaseRanking":20},{"id":59,"createTime":60,"updateTime":61,"relativeEntities":798,"label":799,"description":800,"key":68,"publicationTags":801,"standard":20},[],{"EN":64,"VI":64},{"VI":66,"EN":67},[70,71],[74],{"id":76,"indexDatabase":804,"url":89,"indexYears":90,"academicFieldIds":809,"indexDatabaseRanking":93},{"id":78,"createTime":79,"updateTime":80,"relativeEntities":805,"label":806,"description":807,"key":86,"publicationTags":808,"standard":20},[],{"EN":83,"VI":83},{"EN":83,"VI":85},[88],[92],{"impactFactor":21,"impactFactorByYear":811,"i10Index":21,"i10IndexLast5Year":21,"totalPublication":97,"totalPublicationByYear":812,"totalCitation":21,"totalCitationByYear":813,"totalCitationPerPublication":21,"totalCitationPerPublicationByYear":814,"hindexLast5Year":21,"hindex":21},{},{"1995":99,"1998":100,"1999":99,"2001":100,"2002":100,"2003":100,"2004":100,"2011":100,"2013":100,"2017":100,"2018":99,"2020":100,"2021":99,"2022":101},{},{},{"volume":816,"pages":818},{"VOID":817},"24",{"VOID":819},"1-14","2020-08-31",2020,{"id":823,"createTime":824,"updateTime":825,"relativeEntities":826,"slug":827,"properties":828,"entityType":124,"verifyStatus":125,"verifyTime":825,"verifyNote":126,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":837,"fullTextUrl":20,"authors":838,"publicationType":170,"publisherRelationship":897,"citationCount":20,"citationInfo":20,"publishDate":930,"publishYear":931,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":20,"openAccess":20,"references":20,"isForceReanalyzing":207},"3dac5105-9572-4dc3-8165-f673d94e408b","2024-02-08T13:15:45.010+00:00","2024-08-30T23:54:13.210+00:00",[],"On-the-accuracy-of-the-GPS-L2-observable-for-ionospheric-monitoring",{"references":829,"abstract":831,"title":833,"doi":835},{"VOID":830},"Al-Fanek O, Skone S, Lachapelle G, Fenton P (2007) Evaluation of L2C observations and limitations. In: Proceedings of ION GNSS 2007, Institute of Navigation, Fort Worth, Texas, USA, 25–28 Sept, pp 2510–2518\nBhattacharyya A, Beach TL, Basu S, Kintner PM (2000) Nighttime equatorial ionosphere: GPS scintillations and differential carrier phase fluctuations. Radio Sci 35(1):209–224. https:\u002F\u002Fdoi.org\u002F10.1029\u002F1999rs002213\nCarrano CS, Groves KM, McNeil JW, Doherty PH (2013) Direct measurement of the residual in the ionosphere-free linear combination during scintillation. In: Proceedings of ION ITM 2013, Institute of Navigation, San Diego, California, USA, 28–30 Jan, pp 585–596\nDatta-Barua S, Walter T, Blanch J, Enge P (2008) Bounding higher-order ionosphere errors for the dual-frequency GPS user. Radio Sci. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2007rs003772\nJayachandran PT, Langley RB, MacDougall JW, Mushini SC, Pokhotelov D, Hamza AM, Mann IR, Milling DK, Kale ZC, Chadwick R, Kelly T (2009) Canadian high arctic ionospheric network (CHAIN). Radio Sci. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2008rs004046\nKim D, Serrano L, Langley R (2006) Phase wind-up analysis: assessing real—time kinematic performance. GPS World 17(9):58–64\nKomjathy A (1997) Global ionospheric total electron content mapping using the global positioning system. Ph.D. dissertation, Department of Geodesy and Geomatics Engineering, Technical report no. 188, University of New Brunswick, Fredericton, Canada\nKrankowski A, Cherniak I, Zakharenkova I (2017) The new IGS ionospheric product—TEC fluctuation maps and their scientific application. Abstracts of EGU General Assembly, Vienna, 23–28 Apr, p 8109\nLim D, Moon S, Park C, Lee S (2006) L1\u002FL2CS GPS receiver implementation with fast acquisition scheme. In: IEEE\u002FION plans 2006, Institute of Navigation, Coronado, California, USA, 25–27 Apr. https:\u002F\u002Fdoi.org\u002F10.1109\u002Fplans.2006.1650683\nLiu Z, Yang Z, Chen W (2017) A study on ionospheric irregularities and associated scintillations using multi-constellation GNSS observations. In: Proceedings of ION PNT, Institute of Navigation, Honolulu, Hawaii, USA, 1–4 May 2017\nMitchell CN, Alfonsi L, Franceschi GD, Lester M, Romano V, Wernik AW (2005) GPS TEC and scintillation measurements from the polar ionosphere during the October 2003 storm. Geophys Res Lett. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2004gl021644\nMontenbruck O, Steigenberger P, Prange L, Deng Z, Zhao Q, Perosanz F, Romero I, Noll C, Sturze A, Weber G, Schmid R (2017) The multi-GNSS experiment (MGEX) of the international GNSS service (IGS)—achievements, prospects and challenges. Adv Space Res 59(7):1671–1697. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.asr.2017.01.011\nPi X, Mannucci AJ, Lindqwister UJ, Ho CM (1997) Monitoring of global ionospheric irregularities using the worldwide GPS network. Geophys Res Lett 24(18):2283–2286. https:\u002F\u002Fdoi.org\u002F10.1029\u002F97gl02273\nPrikryl P, Jayachandran PT, Mushini SC, Chadwick R (2011) Climatology of GPS phase scintillation and HF radar backscatter for the high-latitude ionosphere under solar minimum conditions. Ann Geophys 29(2):377–392. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fangeo-29-377-2011\nVan Dierendonck AJ, Klobuchar J, Hua Q (1993) Ionospheric scintillation monitoring using commercial single frequency C\u002FA code receivers. In: Proceedings of ION GPS 1993, Salt Lake City, Utah, pp 1333–1342\nWoo KT (2000) Optimum semicodeless carrier phase tracking of L2. Navigation 47(2):82–99. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fj.2161-4296.2000.tb00204.x\nYang Z, Liu Z (2016) Investigating the inconsistency of ionospheric ROTI indices derived from GPS modernized L2C and legacy L2 P(Y) signals at low-latitude regions. GPS Solut 21(2):783–796. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-016-0568-3",{"EN":832},"The introduction of the unencrypted global positioning system (GPS) L2 civil (L2C) signal has the potential to improve measurements made with the L2 frequency, an important observable in GPS-based ionospheric research and monitoring. Recent work has shown significant differences between the legacy L2P(Y) and L2C-derived total electron content rate of change index (ROTI). This difference is observed between L2P(Y) and L2C-derived ROTI with certain receiver models and between zero-baseline receiver pairs. We discuss the likely cause for these differences: L1-aided tracking used to track both the L2P(Y) and L2C signals. We also present L2C data that are confirmed to be from tracking independent of L1. Using the ionospheric-free linear combination, we show that the independently tracked carrier phase dynamics are significantly more accurate than the L1-aided observables. This result is confirmed by comparing the behavior of the L2C and L2P(Y) carrier phase observables upon a sudden antenna rotation.\n",{"EN":834},"On the accuracy of the GPS L2 observable for ionospheric monitoring",{"VOID":836},"10.1007\u002Fs10291-017-0688-4","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10291-017-0688-4",[839,855,870,882],{"id":840,"sortIndex":21,"researcher":20,"roles":841,"affiliations":842,"properties":852},"37af7f84-13fd-45e8-a9c0-a9d59bc6193e",[132],[843],{"id":20,"sortIndex":21,"affiliation":844,"properties":20},{"id":845,"createTime":846,"updateTime":846,"relativeEntities":847,"slug":848,"properties":849,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"4533fbbf-b9b0-4434-9d2f-6cb69c6816b6","2024-04-15T07:58:21.955+00:00",[],"Department-of-Physics-University-of-New-Brunswick-Fredericton-Canada-",{"title":850},{"EN":851},"Department of Physics, University of New Brunswick, Fredericton (Canada)",{"title":853},{"VI":854},"Anthony M. McCaffrey",{"id":856,"sortIndex":101,"researcher":20,"roles":857,"affiliations":858,"properties":867},"e2dfdb30-2214-4996-908d-a7810aa9477d",[132],[859],{"id":20,"sortIndex":21,"affiliation":860,"properties":20},{"id":861,"createTime":862,"updateTime":862,"relativeEntities":863,"slug":20,"properties":864,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"a8e420a2-ca69-40b9-bad4-d2d45f30a57b","2024-02-08T13:15:45.215+00:00",[],{"title":865},{"VI":866},"Septentrio, Heverlee, Belgium",{"title":868},{"VI":869},"Jean-Marie Sleewaegen",{"id":871,"sortIndex":100,"researcher":20,"roles":872,"affiliations":873,"properties":879},"faac5c5c-3048-45ac-82db-91a7dc2c510c",[132],[874],{"id":20,"sortIndex":21,"affiliation":875,"properties":20},{"id":845,"createTime":846,"updateTime":846,"relativeEntities":876,"slug":848,"properties":877,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":878},{"EN":851},{"title":880},{"VI":881},"P. T. Jayachandran",{"id":883,"sortIndex":99,"researcher":20,"roles":884,"affiliations":885,"properties":894},"32830d00-c35c-423b-9643-2faa57751089",[132],[886],{"id":20,"sortIndex":21,"affiliation":887,"properties":20},{"id":888,"createTime":889,"updateTime":889,"relativeEntities":890,"slug":20,"properties":891,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"bfa965ee-7133-4b5b-8571-360f0eb9df65","2023-12-27T02:28:52.081+00:00",[],{"title":892},{"VI":893},"Department of Geodesy and Geomatics Engineering, University of New Brunswick, Fredericton, Canada",{"title":895},{"VI":896},"Richard B. Langley",{"url":837,"publisher":898,"properties":926},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":899,"slug":10,"properties":900,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":904,"manageAffiliations":905,"indexDatabases":906,"url":94,"thumbnailPath":20,"statistic":921,"gsStatistic":20,"type":104,"analyzePriority":20},[],{"issn":901,"eissn":902,"title":903},{"VOID":13},{"VOID":15},{"EN":17},[],[],[907,914],{"id":57,"indexDatabase":908,"url":72,"indexYears":20,"academicFieldIds":913,"indexDatabaseRanking":20},{"id":59,"createTime":60,"updateTime":61,"relativeEntities":909,"label":910,"description":911,"key":68,"publicationTags":912,"standard":20},[],{"EN":64,"VI":64},{"VI":66,"EN":67},[70,71],[74],{"id":76,"indexDatabase":915,"url":89,"indexYears":90,"academicFieldIds":920,"indexDatabaseRanking":93},{"id":78,"createTime":79,"updateTime":80,"relativeEntities":916,"label":917,"description":918,"key":86,"publicationTags":919,"standard":20},[],{"EN":83,"VI":83},{"EN":83,"VI":85},[88],[92],{"impactFactor":21,"impactFactorByYear":922,"i10Index":21,"i10IndexLast5Year":21,"totalPublication":97,"totalPublicationByYear":923,"totalCitation":21,"totalCitationByYear":924,"totalCitationPerPublication":21,"totalCitationPerPublicationByYear":925,"hindexLast5Year":21,"hindex":21},{},{"1995":99,"1998":100,"1999":99,"2001":100,"2002":100,"2003":100,"2004":100,"2011":100,"2013":100,"2017":100,"2018":99,"2020":100,"2021":99,"2022":101},{},{},{"volume":927,"pages":928},{"VOID":202},{"VOID":929},"1-7","2017-11-30",2017,{"id":933,"createTime":934,"updateTime":934,"relativeEntities":935,"slug":20,"properties":936,"entityType":124,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":945,"fullTextUrl":20,"authors":946,"publicationType":170,"publisherRelationship":1008,"citationCount":20,"citationInfo":20,"publishDate":1042,"publishYear":1043,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":20,"openAccess":20,"references":20,"isForceReanalyzing":207},"890bfd77-0cce-489e-b7bd-193bb432f370","2024-01-17T23:53:12.641+00:00",[],{"references":937,"abstract":939,"title":941,"doi":943},{"VOID":938},"Alonso-Arroyo A, Camps A, Park H, Pascual D, Onrubis R, Martin F (2015) Retrieval of significant wave height and mean sea surface level using the GNSS-R interference pattern technique: results from a three-month field campaign. IEEE Trans Geosci Remote Sens 53(6):3198–3209. https:\u002F\u002Fdoi.org\u002F10.1109\u002FTGRS.2014.2371540\nAlonso-Arroyo A, Zavorotny VU, Camps A (2017) Sea ice detection using UK TDS-1 GNSS-R data. IEEE Trans Geosci Remote Sens 55:3782–3788. https:\u002F\u002Fdoi.org\u002F10.1109\u002FTGRS.2017.2699122\nAttali JG, Pages G (1997) Approximations of functions by a multilayer perceptron: a new approach. Neural Netw 10(6):1069–1081. https:\u002F\u002Fdoi.org\u002F10.1016\u002FS0893-6080(97)00010-5\nBeckmann P, Spizzichino A (1963) The scattering of electromagnetic waves from rough surfaces. Pergamon, New York\nCamps A, Park H, Pablos M, Foti G, Gommenginger PG, Liu PW, Judge J (2016) Sensitivity of GNSS-R spaceborne observations to soil moisture and vegetation. IEEE J Sel Top Appl Earth Observ Remote Sens 9:4730–4742. https:\u002F\u002Fdoi.org\u002F10.1109\u002FJSTARS.2016.2588467\nCardellach E, Fabra F, Rius A, Pettinato S, D’Addio S (2012) Characterization of dry-snow sub-structure using GNSS reflected signals. Remote Sens Environ 124:122–134. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.rse.2012.05.012\nChen Q, Won D, Akos DM (2017) Snow depth estimation accuracy using a dual-interface GPS-IR model with experimental results. GPS Solut 21:211–223. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-016-0517-1\nExpedition M (2022) MOSAiC expedition web page. https:\u002F\u002Ffollow.mosaic-expedition.org\u002F. Accessed on 22 June 2022\nFabra F, Cardellach E, Rius A, Ribo S, Oliveras S, Nogues-Correig O, Rivas MB, Semmling M, D’Addio S (2012) Phase altimetry with dual polarization GNSS-R over sea ice. IEEE Trans Geosci Remote Sens 50:2112–2121. https:\u002F\u002Fdoi.org\u002F10.1109\u002FTGRS.2011.2172797\nFoti G, Gommenginger C, Jales P, Unwin M, Shaw A, Robertson C, Rosello J (2015) Spaceborne GNSS reflectometry for ocean winds: first results from the UK TechDemoSat-1 mission. Geophys Res Lett 43:767–774. https:\u002F\u002Fdoi.org\u002F10.1002\u002F2015GL064204\nGao F, Wang X, Gao Y, Dong J (2019) Sea ice change detection in SAR images based on convolutional-wavelet neural network. IEEE Geosci Remote Sens Lett 16:1240–1244. https:\u002F\u002Fdoi.org\u002F10.1109\u002FLGRS.2019.2895656\nGhiasi Y, Duguay CR, Murfitt J, Sanden JJ, Thompson A, Drouin H, Prevost C (2020) Application of GNSS interferometric reflectometry for the estimation of lake ice thickness. Remote Sens 12:2721. https:\u002F\u002Fdoi.org\u002F10.3390\u002Frs12172721\nHallikainen M, Winebrenner DP (1992) The physical basis for sea ice remote sensing. In: Carsey FD (ed) Microwave remote sensing of sea ice. Wiley, Hoboken, NJ. https:\u002F\u002Fdoi.org\u002F10.1029\u002FGM068p0029\nHaupt SE, Pasini A, Marzban C (2009) Artificial intelligence methods in the environmental science. Springer, Berlin, pp 3–13. https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-1-4020-9119-3\nJacobson MD (2009) Snow-covered Lake ice in GPS multipath reception-theory and measurement. Adv Space Res 46:221–227. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.asr.2009.10.013\nJacobson MD (2015) Potential for estimating the thickness of freshwater lake ice by GPS interferometric reflectometry. J Geogr Geol 7:10–19. https:\u002F\u002Fdoi.org\u002F10.5539\u002Fjgg.v7n1p10\nKlein L, Swift CT (1977) An improved model for the dielectric constant of sea water at microwave frequencies. IEEE Trans Antennas Propag 2:104–111. https:\u002F\u002Fdoi.org\u002F10.1109\u002FTAP.1977.1141539\nKomjathy A, Maslanik J, Zavorotny VU, Axelrad P, Katzberg SJ (2000) Sea ice remote sensing using surface reflected GPS signals. IGARSS 2000:2855–2857. https:\u002F\u002Fdoi.org\u002F10.1109\u002FIGARSS.2000.860270\nLarson K, Nievinski F (2013) GPS snow sensing: results from the Earthscope Plate Boundary Observatory. GPS Solut 17:41–52. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-012-0259-7\nLaxon SW et al (2013) CryoSat-2 estimates of Arctic Sea ice thickness and volume. Geophys Res Lett 40:732–737. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fgrl.50193\nLi W, Rius A, Fabra F, Cardellach E, Ribo S, Martin-Neira M (2018) Revisiting the GNSS-R waveform statistics and its impact on altimetric retrievals. IEEE Trans Geosci Remote Sens 56:2854–2871. https:\u002F\u002Fdoi.org\u002F10.1109\u002FTGRS.2017.2785343\nMunoz-Martin JF et al (2020) Snow and ice thickness retrievals using GNSS-R: preliminary results of the MOSAiC experiment. Remote Sens 12:4038. https:\u002F\u002Fdoi.org\u002F10.3390\u002Frs12244038\nNievinski FG, Larson KM (2014a) Forward modeling of GPS multipath for near-surface reflectometry and positioning applications. GPS Solut 18:309–322. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-013-0331-y\nNievinski FG, Larson KM (2014b) Inverse modeling of GPS multipath for snow depth estimation-part: formulation and simulations. IEEE Trans Geosci Remote Sens 52:6555–6563. https:\u002F\u002Fdoi.org\u002F10.1109\u002FTGRS.2013.2297681\nPiizzlato L, Howell SEL, Derksen C, Dawson J, Copland L (2014) Changing sea ice conditions and marine transportation activity in Canadian Arctic waters between 1990 and 2012. Clim Change 123(2):161–173. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10584-013-1038-3\nRivas MB, Maslanik JA, Axelrad P (2010) Bistatic scattering of GPS signals off Arctic Sea ice. IEEE Trans Geosci Remote Sens 48:1548–1556. https:\u002F\u002Fdoi.org\u002F10.1109\u002FTGRS.2009.2029342\nRodriguez-Alvarez N et al (2011) Land geophysical parameters retrieval using the interference pattern GNSS-R technique. IEEE Trans Geosci Remote Sens 49(1):71–84. https:\u002F\u002Fdoi.org\u002F10.1109\u002FTGRS.2010.2049023\nRuf CS et al (2016) New ocean winds satellite mission to probe hurricanes and tropical convection. Bull Am Meteorol Soc 97(3):385–395. https:\u002F\u002Fdoi.org\u002F10.1175\u002FBAMS-D-14-00218.1\nStrandberg J, Hobiger T, Hass R (2017) Coastal sea ice detection using ground-based GNSS-R. IEEE Geosci Remote Sens Lett 14:1552–1556. https:\u002F\u002Fdoi.org\u002F10.1109\u002FLGRS.2017.2722041\nTiuri ME, Sihvola A, Nyfors E, Hallikaiken MT (1984) The complex dielectric constant of snow at microwave frequencies. IEEE J Ocean Eng OE-9:377–382. https:\u002F\u002Fdoi.org\u002F10.1109\u002FJOE.1984.1145645\nUlaby FT, Moore RK, Fung AK (1981) Microwave remote sensing: active and passive. Artech House, Norwood, MA (ISBN 978-0-89-006193-0)\nUnwin M, Jales P, Gommenginger C, Foti G, Rosello J (2016) Spaceborne GNSS-reflectometry on TechDemoSat-1: early mission operations and exploitation. IEEE J Sel Top Appl Earth Observ Remote Sens 9(10):4525–4539. https:\u002F\u002Fdoi.org\u002F10.1109\u002FJSTARS.2016.2603846\nWang X, Zhang S, Wang L, He X, Zhang Q (2020) Analysis and combination of multi-GNSS snow depth retrievals in multipath reflectometry. GPS Solut 24:77. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-020-00990-3\nWiehl W, Legresy B, Dietrich R (2003) Potential of reflected GNSS signals for ice sheet remote sensing. Prog Electromagn Res 40:177–205. https:\u002F\u002Fdoi.org\u002F10.2528\u002FPIER02102202\nYan Q, Huang W (2020) Sea ice thickness measurement using spaceborne GNSS-R: first results with TechDemoSat-1 data. IEEE J Sel Top Appl Earth Observ Remote Sens 13:99. https:\u002F\u002Fdoi.org\u002F10.1109\u002FJSTARS.2020.2966880\nYan Q, Huang W, Jin S, Jia Y (2020) Pan-tropical soil moisture mapping based on a three-layer model from CYGNSS GNSS-R data. Remote Sens Environ 247:111944. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.rse.2020.111944\nYu K, Ban W, Zhang X, Yu X (2015) Snow depth estimation based on multipath phase combination of GPS triple-frequency signals. IEEE Trans Geosci Remote Sens 53:5100–5109. https:\u002F\u002Fdoi.org\u002F10.1109\u002FTGRS.2015.2417214\nYu K, Li Y, Chang X (2019) Snow depth estimation based on combination of pseudorange and carrier phase of GNSS dual-frequency signals. IEEE Trans Geosci Remote Sens 57:1817–1828. https:\u002F\u002Fdoi.org\u002F10.1109\u002FTGRS.2018.2869284\nZhang Y, Meng W, Gu Q, Han Y, Hong Z, Cao Y, Xia Q, Wang W (2015) Detection of Bohai bay sea ice using GPS-reflected signals. IEEE J Sel Top Appl Earth Observ Remote Sens 8:39–46. https:\u002F\u002Fdoi.org\u002F10.1109\u002FJSTARS.2014.2357894\nZhang Z, Yu Y, Li X, Hui F, Cheng X, Chen Z (2019) Arctic Sea ice classification using microwave scatterometer and radiometer data during 2002–2017. IEEE Trans Geosci Remote Sens 57:5319–5328. https:\u002F\u002Fdoi.org\u002F10.1109\u002FTGRS.2019.2898872",{"EN":940},"A method for retrieving snow and sea ice thickness is developed and simulations are conducted to evaluate the feasibility of the proposed method. When using a defined envelope amplitude and phase, for the snow-free case, RMSEs of 0.24 and 0.34 m can be obtained; for the snow-covered case, the RMSEs of the retrieved sea ice thickness decrease to 0.45 and 0.48 m, and the RMSEs of the retrieved snow thickness are 0.12 and 0.13 m. A method combining the envelope amplitude and phase is proposed to further improve the retrieval accuracy. The simulated results show that combining these two observables can provide an RMSE of 0.19 m for the snow-free case, and for the snow-covered case, the RMSEs of the retrieved snow and sea ice thicknesses are reduced to 0.09 and 0.42 m, respectively. Furthermore, linear polarization observations are proposed and tested. The vertical polarization shows the best measurement performance. When the envelope amplitude and phase of the vertical polarization carrier to noise ratio (CNR) are combined to retrieve snow and sea ice thicknesses, the RMSEs of the retrieved sea ice thickness for the snow-free case decrease to 0.13, and for the snow-covered case, the RMSEs of the retrieved snow and sea ice thicknesses decrease to 0.07 and 0.17 m, respectively.",{"EN":942},"Can sea ice thickness be retrieved using GNSS-interferometric reflectometry?",{"VOID":944},"10.1007\u002Fs10291-022-01309-0","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10291-022-01309-0",[947,972,984,996],{"id":948,"sortIndex":101,"researcher":20,"roles":949,"affiliations":950,"properties":969},"29b81412-4a03-4940-86a4-624b2c3bc154",[132],[951,959],{"id":20,"sortIndex":21,"affiliation":952,"properties":20},{"id":953,"createTime":954,"updateTime":954,"relativeEntities":955,"slug":20,"properties":956,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"30f65f7a-2c7f-4092-a4ed-552caf3ffa73","2024-01-05T18:48:45.850+00:00",[],{"title":957},{"VI":958},"School of Electronic Information Engineering, Beihang University, Beijing, China",{"id":960,"sortIndex":100,"affiliation":961,"properties":968},"07feeda2-a7f5-4f78-bec3-c2d10c595956",{"id":962,"createTime":963,"updateTime":963,"relativeEntities":964,"slug":20,"properties":965,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"8a8eefca-f6ce-4df0-9854-c974da4b0a57","2024-01-17T23:53:13.003+00:00",[],{"title":966},{"VI":967},"School of Information Science and Engineering, Shandong Agricultural University, Tai’an, China",{},{"title":970},{"VI":971},"Lei 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W (1968) A testing procedure for use in geodetic networks. Delft, Rijkscommissie voor Geodesie\nBanville S, Langley RB (2013) Mitigating the impact of ionospheric cycle slips in GNSS observations. J Geodesy 87(2):179–193\nCai CS, Liu ZZ, Xia PF, Dai WJ (2013) Cycle slip detection and repair for undifferenced GPS observations under high ionospheric activity. GPS Solutions 17(2):247–260\nChen J, Zhang Y, Wang J, Yang S, Dong D, Wang J, Qu W, Wu B (2015) A simplified and unified model of multi-GNSS precise point positioning. Adv Space Res 55(1):125–134\nDai Z, Knedlik S, Loffeld O. (2008). Real-time cycle slip detection and determination for multiple frequency GNSS. Proceeding of the 5th workshop on Positioning, Navigation and Communication 2008. Hannover, 37-43\nDai Z, Knedlik S, Loffeld O. (2009). Instantaneous triple-frequency GPS cycle slip detection and repair. International Journal of Navigation and Observation, 2009\nde Lacy MC, Reguzzoni M, Sansò F, Venuti G (2008) The Bayesian detection of discontinuities in a polynomial regression and its application to the cycle slip problem. J Geodesy 82(9):527–542\nde Lacy MC, Reguzzoni M, Sansò F (2012) Real-time cycle slip detection in triple-frequency GNSS. GPS Solutions 16(3):353–362\nFeng Y, Gu S, Shi C, Rizos C (2013) A reference station-based GNSS computing mode to support unified precise point positioning and real-time kinematic services. J Geodesy 87(10):945–960\nGuo F, Zhang X, Wang J (2015) Timing group delay and differential code bias corrections for BeiDou positioning. J Geodesy 89(5):427–445\nHatch R (1982) The synergism of GPS code and carrier measurements. In: Proceedings of the third international symposium on satellite Doppler positioning at physical sciences laboratory of New Mexico State University, 8–12 Feb, vol. 2, 1213–1232\nHuang L, Lu Z, Zhai G, Ouyang Y, Huang M, Lu X, Wu T, Li K (2016) A new triple-frequency cycle slip detecting algorithm validated with BDS data. GPS Solutions 20(4):761–769\nJu B, Gu D, Chang X, Herring TA, Duan X, Wang Z (2017) Enhanced cycle slip detection method for dual-frequency BeiDou GEO carrier phase observations. GPS Solutions 21(4):761–769\nKouba J. (2009). A guide to using International GNSS Service (IGS) products\nLiu ZZ (2011) A new automated cycle slip detection and repair method for a single dual-frequency GPS receiver. J Geodesy 85(3):171–183\nMelbourne WG. (1985). The case for ranging in GPS-based geodetic systems. In: Proceedings of the first international symposium on precise positioning with the Global Positioning System, Rockville, 373-386\nOdijk D, Zhang B, Khodabandeh A, Odolinski R, Teunissen PJ (2016) On the estimability of parameters in undifferenced, uncombined GNSS network and PPP-RTK user models by means of S-system theory. J Geodesy 90(1):15–44\nRemondi BW (1985) Global Positioning System carrier phase: description and use. J Geodesy 59(4):361–377\nSchönemann E, Becker M, Springer T (2011) A new approach for GNSS analysis in a multi-GNSS and multi-signal environment. Journal of Geodetic Science 1(3):204–214\nShi C, Fan L, Li M, Liu Z, Gu S, Zhong S, Song W (2016) An enhanced algorithm to estimate BDS satellite’s differential code biases. J Geodesy 90(2):161–177\nTakasu T, Yasuda A. (2009). Development of the low-cost RTK-GPS receiver with an open source program package RTKLIB. International symposium on GPS\u002FGNSS, Seogwipo-si Jungmun-dong, Korea, 4–6 November, 4-6\nTeunissen PJ (1997) A canonical theory for short GPS baselines. J Geodesy 71(8):513–525\nTeunissen PJ (1998) Success probability of integer GPS ambiguity rounding and bootstrapping. J Geodesy 72(10):606–612\nTeunissen, PJ. (2010). An integrity and quality control procedure for use in multi sensor integration. In ION GPS Redbook Vol. VII Integrated Systems. Institute of Navigation (ION)\nTeunissen PJ, Verhagen S (2009) The GNSS ambiguity ratio-test revisited: a better way of using it. Survey Review 41(312):138–151\nTu R, Zhang H, Ge M, Huang G (2013) A real-time ionospheric model based on GNSS Precise Point Positioning. Adv Space Res 52(6):1125–1134\nVerhagen S. (2005). The GNSS integer ambiguities: estimation and validation. Ph.D. thesis publications on geodesy, vol 58, Netherlands Geodetic Commission, Delft\nWu Y, Jin S, Wang Z, Liu J (2010) Cycle slip detection using multi-frequency GPS carrier phase observations: a simulation study. Adv Space Res 46(2):144–149\nWübbena G (1985) Software developments for geodetic positioning with GPS using TI-4100 code and carrier measurements. Proceedings of the first international symposium on precise positioning with the global positioning system, Rockville 19:403–412\nZehentner N, Mayer-Gürr T (2015) Precise orbit determination based on raw GPS measurements. J Geodesy 90(3):315–327\nZhang Q, Gui Q (2013) Bayesian methods for outliers detection in GNSS time series. J Geodesy 87(7):609–627\nZhang X, Li X (2012) Instantaneous re-initialization in real-time kinematic PPP with cycle slip fixing. GPS Solutions 16(3):315–327\nZhang X, Li P (2015) Benefits of the third frequency signal on cycle slip correction. GPS Solutions 20(3):451–460\nZhao Q, Guo J, Li M, Qu L, Hu Z, Shi C, Liu J (2013) Initial results of precise orbit and clock determination for COMPASS navigation satellite system. J Geod 87(5):475–486. doi:10.1007\u002Fs00190-013-0622-7\nZhao Q, Sun B, Dai Z, Hu Z, Shi C, Liu J (2015) Real-time detection and repair of cycle slips in triple-frequency GNSS measurements. GPS Solutions 19(3):381–391",{"EN":1054},"GNSS undifferenced signal processing, in which the individual signal of each frequency is treated as independent observable, has drawn increasing interest in GNSS community. However, undifferenced signal processing brings new challenges for cycle slip detection and repair. One important feature is the carrier frequency identification of cycle slips since observations are processed separately. An analysis of real cycle slips in a BDS triple-frequency baseline dataset illustrates the deficiencies in the cycle slip detection process commonly implemented, in the case when cycle slips occur in just one specific carrier frequency. Hence, we propose an improved cycle slip detection and repair approach based on a time-differenced model. Two major advantages characterize this proposed approach. The first one is a significant reduction in false alarms due to carrier frequency identification of cycle slips. Having access to a reliable cycle slip detection method significantly reduces the number of ambiguity parameters to be estimated. The second advantage is the benefit of separating the OSS (Observation at the other frequency of Same Satellite without cycle slip) and OSE (Observation at the Same Epoch from other satellites without cycle slip) from the OCS (Observation with Cycle Slip). The simulation results indicate that separation of the OSS and OSE can significantly improve the model strength of cycle slip estimation, especially OSS. The proposed approach is validated by cycle slip estimation with a real data set. Smaller biases and larger ratio values jointly demonstrate that a much stronger model strength can be achieved. Finally, the cycle slip repair procedure is applied to triple-frequency PPP. The stable and fast convergence, as well as the reduction in standard deviations, proves the efficiency of the proposed approach.",{"EN":1056},"Improved time-differenced cycle slip detect and repair for GNSS undifferenced observations",{"VOID":1058},"10.1007\u002Fs10291-017-0677-7","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10291-017-0677-7",[1061,1076,1088,1110,1122,1141],{"id":1062,"sortIndex":101,"researcher":20,"roles":1063,"affiliations":1064,"properties":1073},"0a53c5a8-020c-4476-b65d-d8f6ddfd6009",[132],[1065],{"id":20,"sortIndex":21,"affiliation":1066,"properties":20},{"id":1067,"createTime":1068,"updateTime":1068,"relativeEntities":1069,"slug":20,"properties":1070,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"8e37096f-d285-4d88-84f4-11cc37900069","2023-12-27T07:30:53.218+00:00",[],{"title":1071},{"VI":1072},"Zhengzhou Institute of Surveying and Mapping, 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Mayer",{"url":1059,"publisher":1154,"properties":1182},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1155,"slug":10,"properties":1156,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":1160,"manageAffiliations":1161,"indexDatabases":1162,"url":94,"thumbnailPath":20,"statistic":1177,"gsStatistic":20,"type":104,"analyzePriority":20},[],{"issn":1157,"eissn":1158,"title":1159},{"VOID":13},{"VOID":15},{"EN":17},[],[],[1163,1170],{"id":57,"indexDatabase":1164,"url":72,"indexYears":20,"academicFieldIds":1169,"indexDatabaseRanking":20},{"id":59,"createTime":60,"updateTime":61,"relativeEntities":1165,"label":1166,"description":1167,"key":68,"publicationTags":1168,"standard":20},[],{"EN":64,"VI":64},{"VI":66,"EN":67},[70,71],[74],{"id":76,"indexDatabase":1171,"url":89,"indexYears":90,"academicFieldIds":1176,"indexDatabaseRanking":93},{"id":78,"createTime":79,"updateTime":80,"relativeEntities":1172,"label":1173,"description":1174,"key":86,"publicationTags":1175,"standard":20},[],{"EN":83,"VI":83},{"EN":83,"VI":85},[88],[92],{"impactFactor":21,"impactFactorByYear":1178,"i10Index":21,"i10IndexLast5Year":21,"totalPublication":97,"totalPublicationByYear":1179,"totalCitation":21,"totalCitationByYear":1180,"totalCitationPerPublication":21,"totalCitationPerPublicationByYear":1181,"hindexLast5Year":21,"hindex":21},{},{"1995":99,"1998":100,"1999":99,"2001":100,"2002":100,"2003":100,"2004":100,"2011":100,"2013":100,"2017":100,"2018":99,"2020":100,"2021":99,"2022":101},{},{},{"volume":1183,"pages":1184},{"VOID":202},{"VOID":1185},"1-13","2017-11-04",{"id":1188,"createTime":1189,"updateTime":1190,"relativeEntities":1191,"slug":1192,"properties":1193,"entityType":124,"verifyStatus":125,"verifyTime":1190,"verifyNote":126,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":1202,"fullTextUrl":20,"authors":1203,"publicationType":170,"publisherRelationship":1288,"citationCount":20,"citationInfo":20,"publishDate":1321,"publishYear":1043,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":20,"openAccess":20,"references":20,"isForceReanalyzing":207},"e977a1b1-6943-4e5d-ad61-bc20fab89831","2024-02-12T15:22:52.876+00:00","2025-02-13T23:41:00.434+00:00",[],"A-new-efficient-fusion-positioning-method-for-single-epoch-multi-GNSS-based-on-the-theoretical-analysis-of-the-relationship-between-ADOP-and-PDOP",{"references":1194,"abstract":1196,"title":1198,"doi":1200},{"VOID":1195},"Bai Z, Zhang Q, Huang G, Jing C, Wang J (2019) Real-time BeiDou landslide monitoring technology of “light terminal plus industry cloud.” Acta Geodaetica Et Cartographica Sinica 48(11):1424–1429\nBevilacqua A, Neri A, De Martino P, Isaia R, Novellino A, Tramparulo F, Vitale S (2020) Radial interpolation of GPS and leveling data of ground deformation in a resurgent caldera: application to Campi Flegrei (Italy). J Geodesy 94(2):24\nBoyd S, Vandenberghe L (2004) Convex optimization. Cambridge University Press, Cambridge\nBrack A (2017) Reliable GPS+BDS RTK positioning with partial ambiguity resolution. GPS Solut 21(3):1083–1092\nHorn R, Johnson C (1999) Matrix analysis. Cambridge University Press, Cambridge\nHorn R, Rhee N, So W (1998) Eigenvalue inequalities and equalities. Linear Algebra Appl 270:29–44\nHuang P, Rizos C, Roberts C (2018) Satellite selection with an end-to-end deep learning network. GPS Solut 22(4):108\nLancaster P, Tismenetsky M (1985) The theory of matrices with applications. Academic Press, San Diego\nLi B, Shen Y (2009) Fast GPS ambiguity resolution constraint to available conditions. Geomat Inf Sci Wuhan Univ 34(1):117–121\nLi B, Feng Y, Shen Y (2010) Three carrier ambiguity resolution: distance-independent performance demonstrated using semi-generated triple frequency GPS signals. GPS Solut 14(2):177–184\nLi J, Yang Y, Xu J, He H, Guo H (2015) GNSS multi-carrier fast partial ambiguity resolution strategy tested with real BDS\u002FGPS dual- and triple-frequency observations. GPS Solut 19(1):5–13\nLiu X, Zhang S, Zhang Q, Ding N, Yang W (2019) A fast satellite selection algorithm with floating high cut-off elevation angle based on ADOP for instantaneous multi-GNSS single-frequency relative positioning. Adv Space Res 63(3):1234–1252\nLiu X, Zhang S, Zhang Q, Zheng N, Zhang W, Ding N (2021) Theoretical analysis of the multi-GNSS contribution to partial ambiguity estimation and R-ratio test-based ambiguity validation. GPS Solut 25(2):52\nMarshall A, Olkin I (1979) Inequalities: theory of majorization and its applications. Academic Press, New York\nNie Z, Gao Y, Wang Z, Ji S (2017) A new method for satellite selection with controllable weighted PDOP threshold. Surv Rev 49(355):285–293\nOdijk D, Teunissen P (2008) ADOP in closed form for a hierarchy of multi-frequency single-baseline GNSS models. J Geodesy 82(8):473–492\nOdolinski R, Teunissen P (2016) Single-frequency, dual-GNSS versus dual-frequency, single-GNSS: a low-cost and high-grade receivers GPS-BDS RTK analysis. J Geodesy 90(11):1255–1278\nOdolinski R, Teunissen P, Odijk D (2015) Combined BDS, Galileo, QZSS and GPS single-frequency RTK. GPS Solut 19(1):151–163\nOdolinski R, Teunissen P, Odijk D (2013) An analysis of combined COMPASS\u002FBeiDou-2 and GPS single- and multiple-frequency RTK positioning. In: Proceedings of ION PNT 2013, Institute of Navigation, Honolulu, Hawaii, USA, April 23–25, pp 69–90\nPhillips A (1984) Geometrical determination of PDOP. Navigation 31(4):329–337\nSchur I (1923) Über eine Klasse von Mittelbildungen mit Anwendungen auf die Determinantentheorie. Sitzungsber Berl Math Ges 22:9–20\nTeunissen P (1995) The least-squares ambiguity decorrelation adjustment: a method for fast GPS integer ambiguity estimation. J Geodesy 70:65–82\nTeunissen P (1997) A canonical theory for short GPS baselines. Part IV: precision versus reliability. J Geodesy 71:513–525\nTeunissen P, Verhagen S (2009) The GNSS ambiguity ratio-test revisited: a better way of using it. Survey Rev 41(312):138–151\nTeunissen P, Odolinski R, Odijk D (2014) Instantaneous BeiDou+GPS RTK positioning with high cut-off elevation angles. J Geodesy 88(4):335–350\nTeunissen P, Joosten P, Tiberius C (1999) Geometry-free ambiguity success rates in case of partial fixing. Proc. ION NTM 1999, Institute of Navigation, San Diego, CA, USA, January 25–27, pp 201–207\nVerhagen S, Teunissen P (2006) New global navigation satellite system ambiguity resolution method compared to existing approaches. J Guid Control Dyn 29(4):981–991\nWang J, Feng Y (2013) Reliability of partial ambiguity fixing with multiple GNSS constellations. J Geodesy 87(1):1–14\nWang K, Teunissen P, El-Mowafy A (2020) The ADOP and PDOP: two complementary diagnostics for GNSS positioning. J Surv Eng 146(2):04020008\nYang Y, Li J, Xu J, Tang J, Guo H, He H (2011) Contribution of the compass satellite navigation system to global PNT users. Chinese Sci Bull 56(26):2813–2819\nZaminpardaz S, Teunissen P, Nadarajah N (2017) GLONASS CDMA L3 ambiguity resolution and positioning. GPS Solut 21(2):535–549",{"EN":1197},"The global navigation satellite system (GNSS) can provide single-epoch differential positioning services for geological disasters with a sudden and instantaneous nature. It needs fast and precise monitoring, which lies in the rapidly and correctly fixing ambiguities of GNSS. Compared to a single-frequency single system (SF-SS), multiple GNSSs (multi-GNSS) can achieve a high success rate (SR), but the positioning becomes time- and power-consuming due to its large number of visible satellites. Satellite selection and partial ambiguity resolution (PAR) can improve the positioning efficiency of multi-GNSS, but they cannot achieve precise and high-SR rapid positioning. How to effectively utilize multi-GNSS observations to achieve fast, precise, and high-SR single-epoch positioning becomes crucial. Hence, the following theory and method are developed. The roles of code and carrier observations in precise and high-SR positioning are theoretically analyzed. Then, the relationships between position dilution of precision and ambiguity dilution of precision (ADOP) are established by adopting the Schur-Horn Theorem, Majorization Theorem, and Weyl Theorem. Based on the above analyses, a PAR method of ADOP-based BeiDou navigation satellite system (BDS)\u002FGalileo system (Galileo) augmenting global positioning system (GPS) (A-GPS\u002FBDS\u002FGalileo) is proposed. The single-epoch relative positioning results of SR, positioning accuracy, time consumption, and the R-ratio test-based fixed reliability demonstrate that A-GPS\u002FBDS\u002FGalileo outperforms the traditional SF-SS and single\u002Fdual-frequency multi-GNSS methods: it can achieve fast and precise positioning with an empirical SR of 100.0%; its R-ratio test-based accept, successfully fixed, failure, detection, and false alarm rates can be up to 98.5%, 100.0%, 0.0%, 0.01%, and 1.5%, respectively.",{"EN":1199},"A new efficient fusion positioning method for single-epoch multi-GNSS based on the theoretical analysis of the relationship between ADOP and PDOP",{"VOID":1201},"10.1007\u002Fs10291-022-01319-y","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10291-022-01319-y",[1204,1231,1250,1269],{"id":1205,"sortIndex":101,"researcher":20,"roles":1206,"affiliations":1207,"properties":1228},"6ae3463c-d19b-4e07-9be2-f9a6f0c39980",[132],[1208,1216],{"id":20,"sortIndex":21,"affiliation":1209,"properties":20},{"id":1210,"createTime":1211,"updateTime":1211,"relativeEntities":1212,"slug":20,"properties":1213,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"e1d63735-3c4d-4e1c-8efc-ef2ebe787671","2023-12-25T11:48:52.110+00:00",[],{"title":1214},{"VI":1215},"Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou, China",{"id":1217,"sortIndex":100,"affiliation":1218,"properties":1227},"0515b0f2-e934-4148-a636-918e2f7ec0e9",{"id":1219,"createTime":1220,"updateTime":1221,"relativeEntities":1222,"slug":1223,"properties":1224,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"22057b3d-12ba-42d1-9e24-cfc96d91ed65","2023-12-25T11:02:00.287+00:00","2024-12-26T04:27:25.589+00:00",[],"School-of-Environment-and-Spatial-Informatics-China-University-of-Mining-and-Technology-Xuzhou-China",{"title":1225},{"VI":1226},"School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China",{},{"title":1229},{"VI":1230},"Shuhui Wu",{"id":1232,"sortIndex":99,"researcher":20,"roles":1233,"affiliations":1234,"properties":1247},"66c2679a-e6f0-419e-9744-fd9f447a5852",[132],[1235,1240],{"id":20,"sortIndex":21,"affiliation":1236,"properties":20},{"id":1210,"createTime":1211,"updateTime":1211,"relativeEntities":1237,"slug":20,"properties":1238,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":1239},{"VI":1215},{"id":1241,"sortIndex":100,"affiliation":1242,"properties":1246},"491451af-5d81-483b-b1ce-aee311241002",{"id":1219,"createTime":1220,"updateTime":1221,"relativeEntities":1243,"slug":1223,"properties":1244,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":1245},{"VI":1226},{},{"title":1248},{"VI":1249},"Shubi Zhang",{"id":1251,"sortIndex":100,"researcher":20,"roles":1252,"affiliations":1253,"properties":1266},"487c175a-2db5-43e9-9534-b7d0dcce6392",[132],[1254,1261],{"id":1255,"sortIndex":100,"affiliation":1256,"properties":1260},"1dfb800e-c240-4ac0-b9ba-c38b1c44439e",{"id":1219,"createTime":1220,"updateTime":1221,"relativeEntities":1257,"slug":1223,"properties":1258,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":1259},{"VI":1226},{},{"id":20,"sortIndex":21,"affiliation":1262,"properties":20},{"id":1210,"createTime":1211,"updateTime":1211,"relativeEntities":1263,"slug":20,"properties":1264,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":1265},{"VI":1215},{"title":1267},{"VI":1268},"Qianxin Wang",{"id":1270,"sortIndex":21,"researcher":20,"roles":1271,"affiliations":1272,"properties":1285},"00aa6d28-6a58-4c7f-af6a-513649ee37ef",[132],[1273,1278],{"id":20,"sortIndex":21,"affiliation":1274,"properties":20},{"id":1210,"createTime":1211,"updateTime":1211,"relativeEntities":1275,"slug":20,"properties":1276,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":1277},{"VI":1215},{"id":1279,"sortIndex":100,"affiliation":1280,"properties":1284},"8ec63fc1-6219-4c51-be5c-29dc2ad23421",{"id":1219,"createTime":1220,"updateTime":1221,"relativeEntities":1281,"slug":1223,"properties":1282,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},[],{"title":1283},{"VI":1226},{},{"title":1286},{"VI":1287},"Xin Liu",{"url":1202,"publisher":1289,"properties":1317},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1290,"slug":10,"properties":1291,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":1295,"manageAffiliations":1296,"indexDatabases":1297,"url":94,"thumbnailPath":20,"statistic":1312,"gsStatistic":20,"type":104,"analyzePriority":20},[],{"issn":1292,"eissn":1293,"title":1294},{"VOID":13},{"VOID":15},{"EN":17},[],[],[1298,1305],{"id":57,"indexDatabase":1299,"url":72,"indexYears":20,"academicFieldIds":1304,"indexDatabaseRanking":20},{"id":59,"createTime":60,"updateTime":61,"relativeEntities":1300,"label":1301,"description":1302,"key":68,"publicationTags":1303,"standard":20},[],{"EN":64,"VI":64},{"VI":66,"EN":67},[70,71],[74],{"id":76,"indexDatabase":1306,"url":89,"indexYears":90,"academicFieldIds":1311,"indexDatabaseRanking":93},{"id":78,"createTime":79,"updateTime":80,"relativeEntities":1307,"label":1308,"description":1309,"key":86,"publicationTags":1310,"standard":20},[],{"EN":83,"VI":83},{"EN":83,"VI":85},[88],[92],{"impactFactor":21,"impactFactorByYear":1313,"i10Index":21,"i10IndexLast5Year":21,"totalPublication":97,"totalPublicationByYear":1314,"totalCitation":21,"totalCitationByYear":1315,"totalCitationPerPublication":21,"totalCitationPerPublicationByYear":1316,"hindexLast5Year":21,"hindex":21},{},{"1995":99,"1998":100,"1999":99,"2001":100,"2002":100,"2003":100,"2004":100,"2011":100,"2013":100,"2017":100,"2018":99,"2020":100,"2021":99,"2022":101},{},{},{"volume":1318,"pages":1319},{"VOID":1039},{"VOID":1320},"1-15","2022-09-10",{"id":1323,"createTime":1324,"updateTime":1325,"relativeEntities":1326,"slug":1327,"properties":1328,"entityType":124,"verifyStatus":125,"verifyTime":1325,"verifyNote":126,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":1337,"fullTextUrl":20,"authors":1338,"publicationType":170,"publisherRelationship":1378,"citationCount":20,"citationInfo":20,"publishDate":1410,"publishYear":1043,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":20,"openAccess":20,"references":20,"isForceReanalyzing":207},"2ee479ac-4b94-4880-945a-d9dbcc052f03","2024-01-17T17:25:55.232+00:00","2025-01-02T23:40:34.102+00:00",[],"Offsets-in-the-EPN-station-position-time-series-resulting-from-antenna-radome-changes-PCC-type-dependent-model-analyses",{"references":1329,"abstract":1331,"title":1333,"doi":1335},{"VOID":1330},"Altamimi Z, Sillard P, Boucher C (2012) ITRF2000: a new release of the international terrestrial reference frame for earth science applications. J Geophys Res. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2001JB000561\nAltamimi Z (2018) EUREF Technical note 1: relationship and transformation between the international and the european terrestrial reference systems. http:\u002F\u002Fetrs89.ensg.ign.fr\u002Fpub\u002FEUREF-TN-1.pdf.\nBilich A, Mader G (2010) GNSS absolute antenna calibration at the national geodetic survey. In: proceedings ION GNSS 2010, institute of navigation, Portland, Oregon, OR, Sept 21–24: 1369–1377.\nBilich A, Mader G, Geoghegan C (2018) 6-axis robot for absolute antenna calibration at the US national geodetic survey. In: presentation at the IGS workshop 2018, Oct 29–Nov 2, 2018, Wuhan, China.\nBöder V, Menge F, Seeber G, Wübbena G, Schmitz M (2001) How to deal with station dependent errors—new developments of the absolute calibration of PCV and phase multipath with a precise robot. Proc of ION GPS 2001 Institute of navigation, Nashville, Tennessee, USA, September 11–14, 2166–2176\nBoehm J, Heinkelmann R, Schuh H (2007) Short note: a global model of pressure and temperature for geodetic applications. J Geodesy 81(10):679–683. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00190-007-0135-3\nBruyninx C, Habrich H, Söhne W, Kenyeres A, Stangl G, Völksen C (2012) Enhancement of the EUREF permanent network services and products. Geodesy Planet Earth IAG Symp Ser 136(2012):27–35. https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-642-20338-1_4\nCaizzone S, Schönfeldt M, Elmarissi W, Circiu MS (2021) Antennas as precise sensors for GNSS reference stations and high-performance PNT applications on earth and in space. Sensors 21(12):4192\nDawidowicz K et al (2021) Preliminary results of an Astri\u002FUWM EGNSS receiver antenna calibration facility. Sensors. https:\u002F\u002Fdoi.org\u002F10.3390\u002Fs21144639\nDilssner F, Seeber G, Wübbena G, Schmitz M (2008) Impact of near-field effects on the GNSS position solution. In: Proceedings of the ION GNSS 2008 institute of navigation, Savannah, Georgia, USA, September 16–19: 612–624\nEckl MC, Snay RA, Soler T, Cline MW, Mader GL (2001) Accuracy of GPS-derived relative positions as a function of interstation distance and observing-session duration. J Geod 75:633–640. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs001900100204\nElósegui P, Davis JL, Jaldehag RTK, Johansson JM, Niell AE, Shapiro II (1995) Geodesy using global positioning system: the effects of signal scattering on estimates of site position. J Geophys Res 100(B7):9921–9934. https:\u002F\u002Fdoi.org\u002F10.1029\u002F95JB00868\nFiruzabadi D, King RW (2012) GPS precision as a function of session duration and reference frame using multi-point software. GPS Solut. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-011-0218-8\nGörres B, Campbell J, Becker M, Siemes M (2006) Absolute calibration of GPS antennas: laboratory results and comparison with field and robot techniques. GPS Solut 10:136–145. https:\u002F\u002Fdoi.org\u002F10.1007\u002F463s10291-005-0015-3\nKallio U, Koivula H, Lahtinen S, Nikkonen V, Poutanen M (2019) Validating and comparing GNSS antenna calibrations. J Geod 93:1–18. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00190-018-1134-2\nKenyeres A, Bruyninx C (2004) EPN coordinate time series monitoring for reference frame maintenance. GPS Solut 8:200–209. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-004-0104-8\nKröger J, Kersten T, Breva Y, Schön S (2021) Multi-frequency multi-GNSS receiver antenna calibration at IfE: concept - calibration results - validation. Adv Space Res 68:4932–4947. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.asr.2021.01.474029\nKrzan G, Dawidowicz K, Wielgosz P (2020) Antenna phase center correction differences from robot and chamber calibrations: the case study LEIAR25. GPS Solut. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-020-0957-5\nLyard L, Lefevre L, Letellier T, Francis O (2006) Modelling the global ocean tides: insights from FES2004. Ocean Dyn 56(5–6):394–415. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10236-006-0086-x\nMader G (1999) GPS antenna calibration at the national geodetic survey. GPS Solut 3:50–58. https:\u002F\u002Fdoi.org\u002F10.1007\u002FPL00012780\nMenge F, Seeber G, Völksen C, Wübbena G, Schmitz M (1998) Results of absolute field calibration of GPS antenna PCV. Proc ION GPS 98:31–38\nMontenbruck O et al (2017) The multi-GNSS experiment (MGEX) of the international GNSS service (IGS) - achievements, prospects and challenges. Adv Space Res 59:1671–1697. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.asr.2017.01.011\nPark KD, Nerem RS, Schenewerk MS, Davis JL (2004b) Site specific multipath characteristics of global IGS and CORS GPS sites. J Geod 77:799–803. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00190-003-0359-9\nPark KD, Elósegui P, Davis JL, Jarlemark POJ, Corey BE, Niell AE, Normandeau JE, Meertens CE, Andreatta VA (2004a) Development of an antenna and multipath calibration system for global positioning system sites. Radio Sci. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2003RS002999\nPetit G, Luzum B (2010) IERS conventions (2010). Technical report 36, Frankfurt am Main: Verlag des Bundesamts für Kartographie und Geodäsie, p 179. ISBN 3-89888-989-6\nSchmitz M, Wuebbena G, Boettcher G (2006) Absolute GNSS antenna calibration with a robot: repeatability of phase variations, calibration of GLONASS and determination of carrier-to-noise pattern. In: IGS workshop 2006 perspectives and visions for 2010 and beyond, May 8–12, 2006, ESOC, Darmstadt, Germany\nSchön S, Kersten T (2014) Comparing antenna phase center corrections: challenges, concepts and perspectives. IGS AC workshop 2014 Link. https:\u002F\u002Fwww.ife.uni-hannover.de\u002Fuploads\u002F tx_tkpublikationen\u002FIGS2014_schoenKersten.pdf\nSpringer TA (2009) NAPEOS—mathematical models and algorithms. Technical note, DOPS-SYS-TN-0100-OPS-GN. http:\u002F\u002Fhpiers.obspm.fr\u002Fcombinaison\u002Fdocumentation\u002Farticles\u002FNAPEOS_MathModels_Algorithms.pdf\nTorres JA et al (2009) Status of the European reference frame (EUREF), observing our changing earth. IAG Symp Ser 133:47–56. https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-540-85426-5\nVázquez B, Guadalupe E, Grejner-Brzeziska D (2012) A case of study for Pseudorange multipath estimation and analysis: TAMDEF GPS network. Geofis Int 51:63–72\nWanninger L (2009) Correction of apparent position shifts caused by GNSS antenna changes. GPS Solut 13:133–139. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-008-0106-z\nWanninger L, Thiemig M, Frevert V (2022) Multi-frequency quadrifilar helix antennas for cm-accurate GNSSpositioning. J Appl Geodesy 16(1):25–35. https:\u002F\u002Fdoi.org\u002F10.1515\u002Fjag-2021-0042\nWilli D, Lutz S, Brockmann E, Rothacher M (2020) Absolute field calibration for multi-GNSS receiver antennas at ETH Zurich. GPS Solut 24:28. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-019-0941-0\nWübbena G, Schmitz M, Warneke A (2019) Geo++ absolute multi frequency GNSS antenna calibration. In: presentation at the EUREF analysis center (AC) workshop, October 16 - 17, 2019, Warsaw, Poland",{"EN":1332},"The EUREF Permanent Network (EPN) currently consists of more than 300 evenly distributed continuously operating Global Navigation Satellite System (GNSS) reference stations. As a result of the continuous modernization of GNSS systems, the equipment of reference stations is subject to changes and upgrades. Changes relating to GNSS receiver antenna replacement are considered the main reason for discontinuities noticed in station position time series. It is assumed that resulting offsets are primarily caused by changes in carrier phase multipath effects after antenna replacement. However, the observed position shifts may also indicate the deficiency in the antenna phase center corrections (PCC) models. In this paper, we identified and interpreted the coordinate shifts caused by antenna\u002Fradome changes at selected EPN stations. The main objective was to investigate the correlation between the offset occurrence and PCC model type (type mean, individual robot-derived, individual chamber-derived) as well as multipath changes after antenna replacement. For the study, GNSS data from 12 EPN stations covering the years 2017–2019 were analyzed. The results proved that the antenna replacement is critical in the context of station coordinates stability and, in most cases, results in visible shifts in the position component time series. For GPS-only solutions, the most stable results were achieved using robot-derived individual PCC models. On the other hand, in the case of GPS + Galileo processing, the most stable results were obtained using chamber-derived individual PCC models. Furthermore, discontinuities due to the antenna change were noticed in the position time series in 75% of GPS + Galileo solutions. On the other hand, multipath changes arising as the result of antenna replacement were responsible, depending on solution type, for 21–42% of variations in the coordinates.",{"EN":1334},"Offsets in the EPN station position time series resulting from antenna\u002Fradome changes: PCC type-dependent model analyses",{"VOID":1336},"10.1007\u002Fs10291-022-01339-8","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10291-022-01339-8",[1339,1354,1366],{"id":1340,"sortIndex":21,"researcher":20,"roles":1341,"affiliations":1342,"properties":1351},"dbdf3d8f-f0ae-4c0e-98eb-d7b2c82e8561",[132],[1343],{"id":20,"sortIndex":21,"affiliation":1344,"properties":20},{"id":1345,"createTime":1346,"updateTime":1346,"relativeEntities":1347,"slug":20,"properties":1348,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"e7531d5c-45d1-48a1-accb-9fdb36da0b51","2024-01-17T17:25:55.268+00:00",[],{"title":1349},{"VI":1350},"Institute of Geodesy and Civil Engineering, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland",{"title":1352},{"VI":1353},"K. 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