[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"_public_publisher_byId_43d079e1-0898-46e5-a589-78aa703fe01a":3,"_public_publication_all{\"sortAscending\":false,\"sortField\":\"updateTime\",\"page\":0,\"size\":10,\"facet\":true,\"searchKey\":\"publisherId:43d079e1-0898-46e5-a589-78aa703fe01a,\"}":24},{"code":4,"data":5,"meta":17},"SUCCESS",{"id":6,"createTime":7,"updateTime":7,"relativeEntities":8,"slug":9,"properties":10,"entityType":15,"verifyStatus":16,"verifyTime":17,"verifyNote":17,"syncStatus":16,"languages":17,"translateLanguages":17,"viewCount":18,"subjectFields":19,"manageAffiliations":20,"indexDatabases":21,"url":22,"thumbnailPath":17,"statistic":17,"gsStatistic":17,"type":23,"analyzePriority":17},"43d079e1-0898-46e5-a589-78aa703fe01a","2025-10-14T02:42:39.021+00:00",[],"Journal-of-Military-Science-and-Technology",{"issn":11,"title":13},{"VOID":12},"18591043",{"VOID":14},"Journal of Military Science and Technology","PUBLISHER","PENDING",null,0,[],[],[],"https:\u002F\u002Fonline.jmst.info\u002Findex.php\u002Fjmst","JOURNAL",{"meta":25,"data":27},{"total":26},"1",[28],{"id":29,"createTime":30,"updateTime":31,"relativeEntities":32,"slug":33,"properties":34,"entityType":45,"verifyStatus":46,"verifyTime":47,"verifyNote":48,"syncStatus":16,"languages":49,"translateLanguages":17,"viewCount":18,"primaryUrl":51,"fullTextUrl":17,"authors":52,"publicationType":100,"publisherRelationship":101,"citationCount":17,"citationInfo":17,"publishDate":115,"publishYear":116,"citationAnalyzeStatus":16,"lastCitationAnalyze":17,"indexDatabases":17,"openAccess":17,"references":117,"isForceReanalyzing":138},"4599f8a4-8f41-4c92-8677-fb7ad0bf4c8e","2025-08-28T11:55:56.100+00:00","2025-10-14T02:42:38.988+00:00",[],"An-enhanced-random-noise-suppression-method-for-fiber-optic-gyroscopes-to-improve-gyrocompass-performance",{"keywords":35,"abstract":37,"title":40,"doi":43},{"EN":36},"Gyrocompass; Fiber optic gyroscope; Inertial sensor; Strapdown Inertial Navigation System (SINS); Adaptive Kalman filter.",{"VI":38,"EN":39},"Bài báo này trình bày một phương pháp giảm nhiễu ngẫu nhiên và độ bất ổn định độ trôi điểm 0 trong tín hiệu của con quay sợi quang trên cơ sở thuật toán kết hợp mô hình toán tự hồi quy với bộ lọc Kalman thích nghi và sử dụng cửa sổ trượt Sage. Kết quả của bài báo giúp rút ngắn được thời gian khởi động của gyrocompass mà vẫn bảo đảm độ chính xác của các tham số định hướng ban đầu, đặc biệt là góc phương vị ban đầu. Trên cơ sở đó nâng cao hiệu quả cho gyrocompass trong hệ thống dẫn đường quán tính không đế, đặc biệt trong các trường hợp cần khởi động nhanh.","This paper presents a method for reducing random noise and zero-bias instability in the signal of a fiber optic gyroscope, based on a hybrid algorithm that combines an autoregressive mathematical model with an adaptive Kalman filter using a Sage sliding window. The results of the study demonstrate that this approach shortens the gyrocompass initialization time while maintaining the accuracy of defining initial orientation parameters, particularly the initial azimuth angle. Consequently, it enhances the overall performance of the gyrocompass in strapdown inertial navigation systems, especially in scenarios requiring rapid startup.",{"VI":41,"EN":42},"Phương pháp giảm nhiễu ngẫu nhiên con quay sợi quang nâng cao hiệu quả cho gyrocompass","An enhanced random noise suppression method for fiber optic gyroscopes to improve gyrocompass performance",{"VOID":44},"10.54939\u002F1859-1043.j.mst.105.2025.52-59","PUBLICATION","VERIFIED","2025-08-28T11:55:56.068+00:00","Auto Verify",[50],"EN","https:\u002F\u002Fonline.jmst.info\u002Findex.php\u002Fjmst\u002Farticle\u002Fview\u002F1716",[53,72,86],{"id":54,"sortIndex":18,"researcher":17,"roles":55,"affiliations":56,"properties":69},"0634d8d0-0d70-4ea9-a92d-3a1da75868d7",[],[57],{"id":58,"sortIndex":18,"affiliation":59,"properties":17},"db56233e-8a82-4592-a640-1efbe586efce",{"id":60,"createTime":61,"updateTime":62,"relativeEntities":63,"slug":64,"properties":65,"entityType":68,"verifyStatus":16,"verifyTime":17,"verifyNote":17,"syncStatus":16,"languages":17,"translateLanguages":17,"viewCount":18},"77dff658-53a7-4203-9492-19bdfbded277","2026-04-17T07:23:20.662+00:00","2026-06-19T00:57:37.942+00:00",[],"Institute-of-Missile-Academy-of-Military-Science-and-Technology",{"title":66},{"EN":67},"Institute of Missile\u002FAcademy of Military Science and Technology","AFFILIATION",{"title":70},{"EN":71},"Nguyen Trong Yen",{"id":73,"sortIndex":74,"researcher":17,"roles":75,"affiliations":76,"properties":83},"c15eee36-2c00-460b-8c70-c4ec647a762b",2,[],[77],{"id":78,"sortIndex":18,"affiliation":79,"properties":17},"4ae66ea2-27a7-417c-bd68-b4860bb6894c",{"id":60,"createTime":61,"updateTime":62,"relativeEntities":80,"slug":64,"properties":81,"entityType":68,"verifyStatus":16,"verifyTime":17,"verifyNote":17,"syncStatus":16,"languages":17,"translateLanguages":17,"viewCount":18},[],{"title":82},{"EN":67},{"title":84},{"EN":85},"Đoàn Kết Vũ",{"id":87,"sortIndex":88,"researcher":17,"roles":89,"affiliations":90,"properties":97},"447db094-a0c0-4733-92af-9db56055d083",1,[],[91],{"id":92,"sortIndex":18,"affiliation":93,"properties":17},"fa58876b-df27-4337-bbe0-c71d7fa785bc",{"id":60,"createTime":61,"updateTime":62,"relativeEntities":94,"slug":64,"properties":95,"entityType":68,"verifyStatus":16,"verifyTime":17,"verifyNote":17,"syncStatus":16,"languages":17,"translateLanguages":17,"viewCount":18},[],{"title":96},{"EN":67},{"title":98},{"EN":99},"Nguyen Sy Long","ARTICLE",{"url":17,"publisher":102,"properties":110},{"id":6,"createTime":7,"updateTime":7,"relativeEntities":103,"slug":9,"properties":104,"entityType":15,"verifyStatus":16,"verifyTime":17,"verifyNote":17,"syncStatus":16,"languages":17,"translateLanguages":17,"viewCount":18,"subjectFields":107,"manageAffiliations":108,"indexDatabases":109,"url":22,"thumbnailPath":17,"statistic":17,"gsStatistic":17,"type":23,"analyzePriority":17},[],{"issn":105,"title":106},{"VOID":12},{"VOID":14},[],[],[],{"volume":111,"pages":113},{"VOID":112},"105",{"VOID":114},"52-59","2025-08-25",2025,[118,120,122,124,126,128,130,132,134,136],{"id":17,"text":119,"url":17,"identifiers":17},"[1]. В. В. Матвеев, В. Я. Распопов, “Основы по-строения бесплатформенных инерциальных нави-гационных систем,” СПб: РНЦ РФ ОАО «Концерн «ЦНИИ «Электроприбор», с. 159-161, (2009).",{"id":17,"text":121,"url":17,"identifiers":17},"[2]. Shipeng Han, Zhen Meng, Olatunji Omisore, Toluwanimi Akinyemi, Yuepeng Yan, “ Random Error Reduction Algorithms for MEMS Inertial Sensor Accuracy Improvement,” A Review. Micromachines, vol. 11, iss. 11, pp. 1021-1057, (2020). doi: 10.3390\u002Fmi11111021,.",{"id":17,"text":123,"url":17,"identifiers":17},"[3]. N. T. Yen, A. M. Boronakhin, R. V. Shalymov, D. Y. Larionov, N. Q. Khanh, “Comparison of Adaptive Kalman Filters for Suppressing Random Noise of Optical Gyroscopes in Inertial Navigation,” IEEE Seminar on Signal Processing, (2023), doi: 10.1109\u002FIEEECONF60473.2023.10366085, pp. 87-91.",{"id":17,"text":125,"url":17,"identifiers":17},"[4]. Lei Huang., “Auto Regressive Moving Average (ARMA) Modeling Method for Gyro Random Noise Using a Robust Kalman Filter,” Sensors, vol. 15, iss. 10, pp. 25277–25286, (2015). doi:10.3390\u002Fs151025277.",{"id":17,"text":127,"url":17,"identifiers":17},"[5]. Pengfei Wang, Guangchun Li, Yanbin Gao, “A Compensation Method for Gyroscope Random Drift Based on Unscented Kalman Filter and Support Vector Regression Optimized by Adaptive Beetle Antennae Search Algorithm,” Applied Intelligence, vol. 53, pp. 4350–4365, (2022). doi: 10.1007\u002Fs10489-022-03734-7.",{"id":17,"text":129,"url":17,"identifiers":17},"[6]. Sun J., Xu X., Liu Y., Zhang T., Li Y., “FOG Random Drift Signal Denoising Based on the Improved AR Model and Modified Sage-Husa Adaptive Kalman Filter,” Sensors. Vol. 16, no. 7. pp. 1–19, (2016), doi: 10.3390\u002Fs16071073",{"id":17,"text":131,"url":17,"identifiers":17},"[7]. Артамонов Н. В., Ивин Е. А., Курбацкий А. Н., Фантаццини Д., “Введение в анализ временных рядов,” учебное пособие для вузов: Московский государственный университет имени М. В. Ломоносова, Московская школа экономики, Кафедра эконометрики и математических методов экономики. – Вологда : ВолНЦ РАН, c. 18-25, (2021),.",{"id":17,"text":133,"url":17,"identifiers":17},"[8]. Robert Nau, “ARIMA models for time series forecasting,”, (2022). Available at: https:\u002F\u002Fpeople.duke.edu\u002F~rnau\u002F411arim3.htm.",{"id":17,"text":135,"url":17,"identifiers":17},"[9]. Shesheng Gao, Wenhui Wei, Yongmin Zhong, Subic A., “Sage Windowing and Random Weighting Adaptive Filtering Method for Kinematic Model Error,” IEEE Transactions on Aerospace and Electronic Systems, vol. 51, no. 2, pp. 1488–1500, (2015). doi: 10.1109\u002FTAES.2015.130656.",{"id":17,"text":137,"url":17,"identifiers":17},"[10]. Научно-производственная Компания \"Оптолинк\", “http:\u002F\u002Fwww.optolink.ru\u002Fen\u002Fproducts\u002Fstrapdown_inertial_navigation_systems.",false]