Cooperative geometric localization for a ground target based on the relative distances by multiple UAVs

Springer Science and Business Media LLC - Tập 62 - Trang 1-10 - 2018
Yaohong Qu1, Feng Zhang1, Xiwei Wu1, Bing Xiao1
1School of Automation, Northwestern Polytechnical University, Xi’an, China

Tóm tắt

Based on the locations of several unmanned aerial vehicles (UAVs) and their relative distances from a target, a ground target cooperative geometric localization method that is more effective than a traditional approach is proposed in this paper. First, an algorithm for determining the location of the target is described. The effectiveness and suitability of the proposed algorithm are then shown. Next, to investigate the location accuracy of the proposed method, the influence of three critical factors, namely, the flight altitude, UAV position errors, and measurement errors, is analyzed. Furthermore, for the required location accuracy, the feasible regions of these factors are determined based on their influence, and the location accuracy will satisfy the requirements if all factors are within the feasible regions. Finally, simulation results from the MATLAB/Simulink toolbox are presented to show the effectiveness of the proposed method and the availability of the feasible regions.

Tài liệu tham khảo

Li P, Yu X, Peng X Y, et al. Fault-tolerant cooperative control for multiple UAVs based on sliding mode techniques. Sci China Inf Sci, 2017, 60: 070204 Zhang Y Z, Hu B, Li J W, et al. UAV multi-mission reconnaissance decision-making under uncertainty environment. J Northwestern Polytechnical Univ, 2016, 34: 1028–1034 He W, Huang H, Chen Y, et al. Development of an autonomous flapping-wing aerial vehicle. Sci China Inf Sci, 2017, 60: 063201 Li C Q, Li X B, Zhang J, et al. Analysis of airborne passive location precision based on multi-static cooperation. Modern Radar, 2017, 39: 11–14 Zhu H M, Wang H Y, Sun S Y. Research on error correction method of single UAV based on Monte Carlo. Sci Tech Eng, 2017, 17: 255–259 Esmailifar S M, Saghafi F. Cooperative localization of marine targets by UAVs. Mech Syst Signal Process, 2017, 87: 23–42 Lee W, Bang H, Leeghim H. Cooperative localization between small UAVs using a combination of heterogeneous sensors. Aerospace Sci Tech, 2013, 27: 105–111 Wang K, Ke Y, Chen B M. Autonomous reconfigurable hybrid tail-sitter UAV U-Lion. Sci China Inf Sci, 2017, 60: 033201 Yang K, An J P, Bu X Y, et al. Constrained total least-squares location algorithm using time-difference-of-arrival measurements. IEEE Trans Veh Technol, 2010, 59: 1558–1562 Melchor-Aguilar D, Niculescu S I. Computing non-fragile PI controllers for delay models of TCP/AQM networks. Int J Control, 2009, 82: 2249–2259 Zhu G, Feng D, Yan Z, et al. TOA localization algorithm using the linear-correction technique. J Xidian Univ, 2015, 42: 22–25, 32 Grewal M S, Weill L R, Andrews A P. Global Positioning Systems, Inertial Navigation, and Integration. Hoboken: John Wiley & Sons, Inc., 2007, 3: 383–384 Li W C, Wei P, Xiao X C. A robust TDOA-based location method and its performance analysis. Sci China Ser F-Inf Sci, 2009, 52: 876–882 Fan X, Younan N H, Taylor C D. A perturbation analysis of the regularized constrained total least squares. IEEE Trans Circ Syst II, 1996, 43: 140–142