A Modified Generalized Least Square Registration Algorithm on WGS-84 Coordinate

Abstract

Abstract: Abstract： Aimed at the low convergence rate and unstable convergence performance of the generalized least squares algorithm on WGS84 coordinate, a modified generalized least square algorithm was proposed which took convergence steps as the weighting factor for measurement accuracy of the generalized least squares algorithm, making measurement accuracy vary with the changes of steps in order to achieve the decrease of the convergence steps and the advance of the stability after convergence. So this algorithm improves the performance of target tracking and positioning. Simulation results show that the modified generalized least square algorithm is superior to the generalized least square algorithm, verifying the feasibility of the proposed algorithm.

Key words: Key words： generalized least squares algorithm, coordinate registration, target tracking, measurement accuracy

CLC Number:

TN 953

LI Jiaqiang1a,2,ZHAO Chunyan1b,2,CHEN Jinli1a,1b,ZHAO Ronghua1b,2. A Modified Generalized Least Square Registration Algorithm on WGS-84 Coordinate[J]. Journal of Shanghai Jiaotong University, 2016, 50(05): 771-775.

References

［1］何友, 修建娟, 张晶炜, 等.雷达数据处理及应用［M］. 第3版.北京:电子工业出版社, 2013: 335340. ［2］徐惠群, 高秉亚. 组网雷达系统误差的估计原理与性能分析［J］. 现代雷达, 2009, 31(5):3942. XU Huiqun, GAO Bingya.Theory of error estimation and its performance for network radar system［J］. Modern Radar, 2009, 31(5):3942. ［3］QIU N, LIU Q S, GAO Q Y, et al. Combining genetic algorithm and generalized least squares for geophysical potential field data optimized inversion［J］. IEEE Geoscience & Remote Sensing Letters, 2010, 7(4):660664. ［4］YOU H, HONGWEI Z, XIAOMING T. Joint systematic error estimation algorithm for radar and automatic dependent surveillance broadcasting［J］. IET Radar, Sonar & Navigation, 2013, 7(4):361370. ［5］CHEN Siyue,GUO Qing，LEUNG H, et al. A maximum likelihood approach to joint image registration and fusion［J］. IEEE Transactions on Image Processing, 2011, 20(5):13631372. ［6］胡洪涛, 敬忠良, 胡士强. 一种基于Unscented卡尔曼滤波的多平台多传感器配准算法［J］. 上海交通大学学报, 2005, 39(9):15181521. HU Hongtao, JING Zhongliang, HU Shiqiang. An unscented kalman filter based multiplatform multisensor registration［J］. Journal of Shanghai Jiaotong University, 2005, 39(9):15181521. ［7］胡雷, 林岳松, 郭云飞. 约束总体最小二乘空间配准算法［J］. 火力与指挥控制, 2011, 36(10):58. HU Lei, LIN Yuesong, GUO Yunfei. Space registration algorithm based on constrictive total least squares［J］. Fire Control & Command Control, 2011, 36(10):58. ［8］折晓宇. 多源信息协同处理与融合方法［D］. 西安：西安电子科技大学研究生院, 2013. ［9］SHEN X, ZHANG Y, LU X, et al. An improved method for transforming GPS/INS attitude to national map projection frame［J］. IEEE Geoscience and Remote Sensing Letters, 2015, 12(6): 13021306. ［10］FORTUNATI S, FARINA A, GINI F, et al. Least squares estimation and cramérrao type lower bounds for relative sensor registration process［J］. IEEE Transactions on Signal Processing, 2011, 59(3):10751087. ［11］张翔宇, 王国宏, 李俊杰,等. 临近空间高超声速滑跃式轨迹目标跟踪技术［J］. 航空学报, 2015，36(6):19831994. ZHANG Xiangyu, WANG Guohong, LI Junjie, et al. Tracking of hypersonic sliding target in nearspace［J］. Acta Aeronautica et Astronautica Sinica, 2015,36（6）:19831994. ［12］吴卫华, 江晶, 张忠磊，等. WGS84坐标系下空基多平台有源传感器最大似然配准［J］. 电光与控制, 2014, 21(10):6569. WU Weihua, JIANG Jing, ZHANG Zhonglei, et al. Maximum likelihood registration for active sensors on multiple airborne platforms in WGS84［J］. Electronics Optics & Control, 2014, 21(10):6569.

[1]	HE Zishu, SU Yang, CHENG Ting. Opportunistic Cooperative Target Tracking Algorithm Based on the Co-located MIMO Radar Networking System [J]. Air & Space Defense, 2022, 5(1): 6-11.
[2]	ZHANG Lulu (章露露), DONG Xiangxiang (董祥祥), YAO Lixiu (姚莉秀), CAI Yunze (蔡云泽). Velocity-Varying Target Tracking of Mobile Sensor Network Based on Flocking Control [J]. J Shanghai Jiaotong Univ Sci, 2021, 26(4): 446-453.
[3]	CHEN Xiao，LI Ya’an，LI Yuxing，YU Jing. Maneuvering Target Tracking Algorithm Based on Weighted Distance of Probability Data Association [J]. Journal of Shanghai Jiaotong University, 2018, 52(4): 474-479.
[4]	LI Tantan,LEI Ming. Heuristic Algorithm-Based Initiation Method of Probability Hypothesis Density Filter for Target Tracking [J]. Journal of Shanghai Jiaotong University, 2018, 52(1): 63-69.
[5]	ZHANG Tie，MA Qiongxiong. Human Object Tracking Algorithm for Human-Robot Interaction [J]. Journal of Shanghai Jiaotong University, 2015, 49(08): 1213-1219.
[6]	HOU Jing* (侯静), JING Zhan-rong (景占荣), YANG Yan (羊彦). Target Tracking in Standoff Jammer Using Unscented Kalman Filter and Particle Fiter with Negative Information [J]. Journal of shanghai Jiaotong University (Science), 2014, 19(2): 181-189.
[7]	LIU Shirong1,2，WU Chu1,3,ZHANG Botao1,2,ZHANG Haibing1,2. A Tracking Algorithm Based on SIFT Feature and Particle Filter with Epipolar Constraint [J]. Journal of Shanghai Jiaotong University, 2014, 48(07): 1026-1032.
[8]	JIA Songmin1,WANG Shuang1,WANG Lijia1,2,LI Xiuzhi1. Human Tracking Based on MultiFeature for Intelligent Robot Under the CTF Locating Strategy [J]. Journal of Shanghai Jiaotong University, 2014, 48(07): 1039-1045.
[9]	MA Shan,ZHANG Tiedong,PANG Yongjie,WAN Lei. Acoustic Images Multi-Target Tracking Method Based on Modified Particle Filter [J]. Journal of Shanghai Jiaotong University, 2013, 47(12): 1848-1855.
[10]	ZHANG Zhongde,ZHANG Chongwei . A Method to Improve the Accuracy of Videobased Vehicle Speed Measurement [J]. Journal of Shanghai Jiaotong University, 2010, 44(10): 1439-1443.