TDOA/FDOA passive localization algorithm for moving target with sensor parameter errors

被引：0
|
作者：
Sun T. [1 ]
Dong C. [1 ]
机构：
[1] School of Electronic Engineering, Xidian University, Xi'an
来源：
Dong, Chunxi (chxdong@mail.xidian.edu.cn) | 1600年 / Chinese Society of Astronautics卷 / 41期
关键词：
Cramér-Rao lower bound; Frequency difference of arrival; Passive localization; Sensor position errors; Time difference of arrival;
D O I：
10.7527/S1000-7527.2019.23317
中图分类号：
学科分类号：
摘要：
In a moving target passive localization system, the premise of many algorithms is that the position and velocity of the sensors are accurately known. However, there exists some noise disturbances in the parameters of available sensors. Aiming to solve this problem, an improved Two-Step Weighted Least Squares (TSWLS) localization algorithm using Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA) is proposed. The proposed algorithm is a closed-form solution and is divided into two steps. While the first step is the same as that of the typical TSWLS method, the second step further studies the relationship between the nuisances and the target parameters, establishing a new matrix equation. Then, the final solution is given via Weighted Least Squares (WLS) technique. Theoretical analysis proves that this method can reach the Cramér-Rao Lower Bound (CRLB) at a low noise level. The proposed algorithm in this paper has the advantages of low computational complexity and high real-time performance. In addition, this method is also suitable for locating multiple disjoint sources after appropriate dimensional adjustment. Simulations further demonstrate the effectiveness of the theoretical analysis. © 2020, Press of Chinese Journal of Aeronautics. All right reserved.
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  • [1] Tian Z.C., Liu C.F., Passive Locating Technology, pp. 8-12, (2015)
  • [2] Patwari N., Ash J., Kyperountas S., Et al., Locating the nodes: Cooperative localization in wireless sensor networks, IEEE Signal Process Magazine, 22, 4, pp. 54-69, (2005)
  • [3] Zhu G.H., Feng D.Z., Nie W.K., Multidimensional scaling based TDOA localization algorithm with sensor location errors, Acta Electronica Sinica, 44, 1, pp. 21-26, (2016)
  • [4] Le T.K., Ho K.C., Uncovering source ranges from range differences observed by sensors at unknown positions: Fundamental theory, IEEE Transactions on Signal Processing, 67, 10, pp. 2665-2678, (2019)
  • [5] Hao B.J., Gu L.M., Li Z., Et al., Passive radar source localisation based on PSAAA using single small size aircraft, IET Signal Processing, 10, 7, pp. 1191-1200, (2016)
  • [6] Zhu J.F., Chen Y., Hao B.J., Passive radar source localization using synthetic aperture antenna array, Acta Electronica Sinica, 45, 10, pp. 22-26, (2017)
  • [7] Northard T., Nardone S.C., Track-before-detect bearings-only localization performance in complex passive sonar scenarios: A case study, IEEE Journal of Oceanic Engineering, 44, 2, pp. 482-491, (2019)
  • [8] Liu H.P., Sun F.C., Fang B., Et al., Robotic room-level localization using multiple sets of sonar measurements, IEEE Transactions on Instrumentation and Measurements, 66, 1, pp. 2-13, (2017)
  • [9] Salvati D., Drioli C., Foresti G.L., Sound source and microphone localization from acoustic impulse responses, IEEE Signal Processing Letters, 23, 10, pp. 1459-1463, (2016)
  • [10] Foy W.H., Position-location solutions by Taylor-series estimation, IEEE Transactions on Aerospace & Electronic Systems, 12, 2, pp. 187-194, (1987)
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