Volume 5 Issue 3
Jun.  2016
Turn off MathJax
Article Contents

Zhao Yongsheng, Zhao Yongjun, Zhao Chuang. Weighted Least Squares Algorithm for Single-observer Passive Coherent Location Using DOA and TDOA Measurements[J]. Journal of Radars, 2016, 5(3): 302-311. doi: 10.12000/JR15133
Citation: Zhao Yongsheng, Zhao Yongjun, Zhao Chuang. Weighted Least Squares Algorithm for Single-observer Passive Coherent Location Using DOA and TDOA Measurements[J]. Journal of Radars, 2016, 5(3): 302-311. doi: 10.12000/JR15133

Weighted Least Squares Algorithm for Single-observer Passive Coherent Location Using DOA and TDOA Measurements

doi: 10.12000/JR15133
Funds:

The National High Technology Research and Development Program of China (2012AA7031015), The National Natural Science Foundation of China (61401469, 41301481, 61501513)

  • Received Date: 2015-12-28
  • Rev Recd Date: 2016-02-01
  • Publish Date: 2016-06-28
  • In order to determine single-observer passive coherent locations using illuminators of opportunity, we propose a jointing angle and Time Difference Of Arrival (TDOA) Weighted Least Squares (WLS) location method. First, we linearize the DOA and TDOA measurement equations. We establish the localization problem as the WLS optimization model by considering the errors in the location equations. Then, we iteratively solve the WLS optimization. Finally, we conduct a performance analysis of the proposed method. Simulation results show that, unlike the TDOA-only method, which needs at least three illuminators to locate a target, the jointing DOA and TDOA method requires only one illuminator. It also has a higher localization accuracy than the TDOA-only method when using the same number of illuminators. The proposed method yields a lower mean square error than the least squares algorithm, which makes it possible to approach the Cramr-Rao lower bound at a relatively high TDOA noise level. Moreover, on the basis of the geometric dilution of precision, we conclude that the positions of the target and illuminators are also important factors affecting the localization accuracy.
  • loading
  • [1] Liu Jun, Li Hong-bin, and Himed B. On the performance of the cross-correlation detector for passive radar applications[J]. Signal Processing, 2015, 113: 32-37.
    [2] 曲付勇, 孟祥伟. 基于约束总体最小二乘方法的到达时差到达频差无源定位算法[J]. 电子与信息学报, 2014, 36(5): 1075-1081. Qu Fu-yong and Meng Xiang-wei. Source localization using TDOA and FDOA measurements based on constrained total least squares algorithm[J]. Journal of Electronics Information Technology, 2014, 36(5): 1075-1081.
    [3] Subedi S, Zhang Y D, Amin M G, et al.. Motion parameter estimation of multiple ground moving targets in multi-static passive radar systems[J]. EURASIP Journal on Advances in Signal Processing, 2014, 2014: 157.
    [4] Palmer J, Palumbo S, Summers A, et al.. An overview of an illuminator of opportunity passive radar research project and its signal processing research directions[J]. Digital Signal Processing, 2011, 21(5): 593-599.
    [5] Ansari F and Taban M R. Clutter and direct signal cancellation in analog TV-based passive radar[J]. Journal of Radar, 2014, 1(2): 1-14.
    [6] You Jun, Wan Xian-rong, Fu Yan, et al.. Experimental study of polarisation technique on multi-FM-based passive radar[J]. IET Radar, Sonar Navigation, 2015, 9(7): 763-771.
    [7] Michael E, Alexander S, and Folker M. Design and performance evaluation of a mature FM/DAB/DVB-T multi-illuminator passive radar system[J]. IET Radar, Sonar Navigation, 2014, 8(2): 114-122.
    [8] Zemmari R, Broetje M, Battistello G, et al.. GSM passive coherent location system: performance prediction and measurement evaluation[J]. IET Radar, Sonar Navigation, 2014, 8(2): 94-105.
    [9] Falcone P, Colone F, Macera A, et al.. Two-dimensional location of moving targets within local areas using WiFi-based multistatic passive radar[J]. IET Radar, Sonar Navigation, 2014, 8(2): 123-131.
    [10] Weiss A J. On the accuracy of a cellular location system based on RSS measurement[J]. IEEE Transactions on Vehicular Technology, 2003, 52(6): 1508-1518.
    [11] Zhong Yu, Wu Xiao-yan, and Huang Cai-shu. Geometric dilution of precision for bearing-only passive location in three-dimensional space[J]. Electronics Letters, 2015, 51(6): 518-519.
    [12] Wu Pan-long, Li Xing-xiu, Zhang Lian-zheng, et al.. Passive location using TDOA measurements from compass satellite illuminators[J]. Asian Journal of Control, 2015, 17(2): 722-728.
    [13] Gaber A and Omar A. A study of wireless indoor positioning based on joint TDOA and DOA estimation using 2-D matrix pencil algorithms and IEEE 802.11ac[J]. IEEE Transactions on Wireless Communications, 2015, 14(5): 2440-2454.
    [14] 李红伟. 外辐射源雷达目标定位与跟踪方法研究[D]. [博士论文], 西安电子科技大学, 2012: 15-39. Li Hong-wei. Studies on target localization and tracking in passive coherent location radar[D]. [Ph.D. dissertation], Xidian University, 2012: 15-39.
    [15] Ho K C, Lu Xiao-ning, and Kovavisaruch L. Source localization using TDOA and FDOA measurements in the presence of receiver location errors: analysis and solution[J]. IEEE Transactions on Signal Processing, 2007, 55(2): 684-696.
    [16] Lin Lanxin, So H C, Chan F K W, et al.. A new constrained weighted least squares algorithm for TDOA-based localization[J]. Signal Processing, 2013, 93(11): 2872-2878.
    [17] Yang Kai, An Jian-ping, Bu Xiang-yuan, et al.. Constrained total least-squares location algorithm using time-difference-of-arrival measurements[J]. IEEE Transactions on Vehicular Technology, 2010, 59(3): 1558-1562.
    [18] Norouzi Y and Derakhshani M. Joint time difference of arrival/angle of arrival position finding in passive radar[J]. IET Radar, Sonar Navigation, 2009, 3(2): 167-176.
    [19] Li Wan-chun, Wei Ping, and Xiao Xian-ci. A robust TDOA-based location method and its performance analysis[J]. Science in China Series F: Information Sciences, 2009, 52(5): 876-882.
    [20] He You, Zhang Cai-sheng, Tang Xiao-ming, et al.. Coherent integration loss due to pulses loss and phase modulation in passive bistatic radar[J]. Digital Signal Processing, 2013, 23(4): 1265-1276.
    [21] 梁浩, 崔琛, 代林, 等. 基于ESPRIT算法的L型阵列MIMO雷达降维DOA估计[J]. 电子与信息学报, 2015, 37(8): 1828-1835. Liang Hao, Cui Chen, Dai Lin, et al.. Reduced-dimensional DOA estimation based on ESPRIT algorithm in MIMO radar with L-shaped array[J]. Journal of Electronics Information Technology, 2015, 37(8): 1828-1835.
    [22] Li Jing, Zhao Yong-jun, and Li Dong-hai. Passive multipath time delay estimation using MCMC methods[J]. Circuits, Systems, and Signal Processing, 2015, 34(12): 3897-3913.
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Article views(1262) PDF downloads(1134) Cited by()

Proportional views
Related

Weighted Least Squares Algorithm for Single-observer Passive Coherent Location Using DOA and TDOA Measurements

doi: 10.12000/JR15133
Funds:

The National High Technology Research and Development Program of China (2012AA7031015), The National Natural Science Foundation of China (61401469, 41301481, 61501513)

Abstract: In order to determine single-observer passive coherent locations using illuminators of opportunity, we propose a jointing angle and Time Difference Of Arrival (TDOA) Weighted Least Squares (WLS) location method. First, we linearize the DOA and TDOA measurement equations. We establish the localization problem as the WLS optimization model by considering the errors in the location equations. Then, we iteratively solve the WLS optimization. Finally, we conduct a performance analysis of the proposed method. Simulation results show that, unlike the TDOA-only method, which needs at least three illuminators to locate a target, the jointing DOA and TDOA method requires only one illuminator. It also has a higher localization accuracy than the TDOA-only method when using the same number of illuminators. The proposed method yields a lower mean square error than the least squares algorithm, which makes it possible to approach the Cramr-Rao lower bound at a relatively high TDOA noise level. Moreover, on the basis of the geometric dilution of precision, we conclude that the positions of the target and illuminators are also important factors affecting the localization accuracy.

Zhao Yongsheng, Zhao Yongjun, Zhao Chuang. Weighted Least Squares Algorithm for Single-observer Passive Coherent Location Using DOA and TDOA Measurements[J]. Journal of Radars, 2016, 5(3): 302-311. doi: 10.12000/JR15133
Citation: Zhao Yongsheng, Zhao Yongjun, Zhao Chuang. Weighted Least Squares Algorithm for Single-observer Passive Coherent Location Using DOA and TDOA Measurements[J]. Journal of Radars, 2016, 5(3): 302-311. doi: 10.12000/JR15133
Reference (22)

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint