一种考虑传感器位置误差的改进源定位算法
收稿日期: 2013-09-21
修回日期: 2014-01-21
网络出版日期: 2014-02-19
An Improved Source Localization Algorithm in Presence of Sensor Location Errors
Received date: 2013-09-21
Revised date: 2014-01-21
Online published: 2014-02-19
在无线传感器网络的定位问题中，通过移动目标与传感器之间的到达时差（TDOA）与到达频差（FDOA）测量量可以估计目标的位置和速度。但是，当传感器自身信息存在误差时，传统的定位方法将失去精确的定位效果。针对带有传感器误差的源定位问题，基于极大似然（ML）法获取一个封闭的近似解。提出了一种改进的近似极大似然（AML）算法，更新带有传感器误差的代价函数，不仅能实现实时定位，而且保证全局收敛。仿真结果表明，本文算法在存在传感器误差场景下依然可以达到克拉美-罗下限（CRLB），比已有的改进两步加权最小二乘（2-step WLS）法更有效。
曹亚陆 , 彭力 . 一种考虑传感器位置误差的改进源定位算法[J]. 航空学报, 2014 , 35(7) : 1992 -1998 . DOI: 10.7527/S1000-6893.2013.0528
The position and velocity of a moving source can be estimated by utilizing the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements between moving targets and sensors in the localization of wireless sensor networks. The traditional localization algorithms will lose accurate positioning effect in the presence of sensor location errors. Based on the maximum likelihood (ML) function, a closed-form approximate solution can be obtained. This paper develops an improved approximate maximum likelihood (AML) algorithm by updating the cost function with sensor uncertainty, which can allow real-time implementation as well as global convergence. Simulation results show that the proposed algorithm can attain the Cramer-Rao lower bound (CRLB) in the presence of sensor location errors, and it performs better than the modified two-step weighted least squares (2-step WLS) approach.
[1] Yick J, Mukherjee B, Ghosal D. Wireless sensor network survey[J]. Computer Networks, 2008, 52(12): 2292-2330.
[2] Mao G, Fidan B, Anderson B D O. Wireless sensor network localization techniques[J]. Computer Networks, 2007, 51(10): 2529-2553.
[3] Sakarindr P, Ansari N. Security services in group communications over wireless infrastructure, mobile ad-hoc, and wireless sensor networks[J]. IEEE Wireless Communications, 2007, 14(5): 8-20.
[4] Nakayama H, Ansari N, Jamalipour A, et al. Fault-resilient sensing in wireless sensor networks[J]. Computer Communications, 2007, 30(11-12): 2375-2384.
[5] Zhang Y, Ansari N, Su W. Optimal decision fusion based automatic modulation classification by using wireless sensor networks in multipath fading channel//IEEE GLOBECOM Proceedings, 2011: 1-5.
[6] Patwari N, Ash J N, Kyperountas S, et al. Locating the nodes: cooperative localization in wirelesss sensor networks[J]. IEEE Signal Processing Magazine, 2005, 22(4): 54-69.
[7] Carter G C. Time delay estimation for passive sonar signal processing[J]. IEEE Transactions on Acoustics, Speech, Signal Processing, 1981, ASSP-29(3): 462-470.
[8] Weinstein E. Optimal source localization and tracking from passive array measurements[J]. IEEE Transactions on Acoustics, Speech, Signal Processing, 1982, ASSP-30(1): 69-76.
[9] Jia X J, Guo F C, Zhou Y Y. Passive localization based on short time TDOA sequence[J]. Acta Aeronautica et Astronautica Sinica, 2011, 32(2): 291-298. (in Chinese) 贾兴江, 郭福成, 周一宇. 基于短时时差序列的无源定位方法[J]. 航空学报, 2011, 32(2): 291-298.
[10] Beck A, Stoica P, Li J. Exact and approximate solutions of source localization problems[J]. IEEE Transactions on Signal Processing, 2008, 56(5): 1770-1778.
[11] Guo F C, Fan Y. A method of dual-satellites geolocations using TDOA and FDOA and its presicion analysis[J]. Journal of Astronautics, 2008, 29(4): 1381-1386. (in Chinese) 郭福成, 樊昀. 双星时差频差联台定位方法及其误差分析[J]. 宇航学报, 2008, 29(4): 1381-1386.
[12] Torrieri D J. Statistical theory of passive location systems[M]. New York: Springer, 1990: 151-166.
[13] Ho K C, Xu W. An accurate algebraic solution for moving source location using TDOA and FDOA measurements[J]. IEEE Transactions on Signal Processing, 2004, 52(9): 2453-2463.
[14] Wei H W, Peng R, Wan Q, et al. Multidimensional scaling analysis for passive moving target localization with TDOA and FDOA measurements[J]. IEEE Transactions on Signal Processing, 2010, 58(3): 1677-1688.
[15] Yu H G, Huang G M, Gao J, et al. Approximate maximum likelihood algorithm for moving source localization using TDOA and FDOA measurements[J]. Chinese Journal of Aeronautics, 2012, 25(4): 593-597.
[16] Chan Y T, Hang H Y C, Ching P C. Exact and approximate maximum likelihood localization algorithms[J]. IEEE Transactions on Vehicular Technology, 2006, 55(1): 10-16.
[17] Ho K C, Xu W. 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.
[18] Lin L X, 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.
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