A robust TDOA based solution for source location using mixed Huber loss

doi:10.23919/JSEE.2021.000117

Journal of Systems Engineering and Electronics ›› 2021, Vol. 32 ›› Issue (6): 1375-1380.doi: 10.23919/JSEE.2021.000117

收稿日期:2020-11-26 出版日期:2022-01-05 发布日期:2022-01-05

A robust TDOA based solution for source location using mixed Huber loss

Mingyi YOU^1,^2,*(), Annan LU^1,²()

¹ Science and Technology on Communication Information Security Control Laboratory, No. 36 Research Institute of China Electronics Technology Group Corporation, Jiaxing 314033, China
² No. 36 Research Institute of China Electronics Technology Group Corporation, Jiaxing 314033, China

Received:2020-11-26 Online:2022-01-05 Published:2022-01-05
Contact: Mingyi YOU E-mail:youmingyi@126.com;luannan1959@163.com
About author:|YOU Mingyi was born in 1984. He received his B.S. and Ph.D. degrees both in mechanical engineering from Shanghai Jiao Tong University, Shanghai, in 2006 and 2012 respectively. He was invited to visit the S. M. Wu Manufacturing Research Center of the University of Michigan from 2007 to 2008. He is currently a senior expert in No.36 Research Institute of China Electronics Technology Group Corporation, leading a research group in radio direction finding and localization. His research interests include condition-based maintenance, radio direction finding, wireless localization and multi-object tracking. E-mail: youmingyi@126.com||LU Annan was born in 1959. He received his B.S. degree in mathematics from Hunan Education College in 1987, and M.S. degree in applied mathematics from Huazhong University of Science and Technology in 1989. He is the chief scientist of China Electronics Technology Group Corporation. His research interests include radio direction finding and passive localization. E-mail: luannan1959@163.com
Supported by:
This work was supported by the National Natural Science Foundation of China (U20B2038)

摘要/Abstract

Abstract:

This paper proposes a source localization solution robust to measurement outliers in time differences of arrivals (TDOA) measurements. The solution uses a piecewise loss function named as mixed Huber loss (MHL) proposed based on the classical Huber loss (HL) and its refined version. The MHL is able to effectively mitigate the impact of all levels of measurement outliers by setting two triggering thresholds. In practice, appropriate triggering threshold values can be obtained through simulation given the level of measurement noise and a rough range of potential measurement outliers. A clustering based approach is proposed to further improve the robustness of localization solution against reference sensor related outliers. Simulations are included to examine the solution’s performance and compare it with several benchmarks. The proposed MHL based solution is shown to be superior to the classical solution and the benchmarks. The solution is shown to be even robust to multiple measurement outliers. Furthermore, the influence of range measurement outliers in the reference sensor can be effectively mitigated by the clustering based approach.

Key words: time differences of arrivals (TDOA), robust localization, Huber loss (HL), outlier mitigation

. [J]. Journal of Systems Engineering and Electronics, 2021, 32(6): 1375-1380.

Mingyi YOU, Annan LU. A robust TDOA based solution for source location using mixed Huber loss[J]. Journal of Systems Engineering and Electronics, 2021, 32(6): 1375-1380.

图/表 9

参考文献 16

1	HO K C, XU W An accurate algebraic solution for moving source location using TDOA and FDOA measurements. IEEE Trans. on Signal Processing, 2004, 52 (9): 2453- 2463. doi: 10.1109/TSP.2004.831921
2	WEISS A J Direct position determination of narrowband radio frequency transmitters. IEEE Signal Processing Letters, 2004, 11 (5): 513- 516. doi: 10.1109/LSP.2004.826501
3	ZHANG S J, GAO S C, WANG G, et al Robust NLOS error mitigation method for TOA-based localization via second-order cone relaxation. IEEE Communication Letters, 2015, 19 (12): 2210- 2213. doi: 10.1109/LCOMM.2015.2482979
4	YANG K H, WANG G, LUO Z Q Efficient convex relaxation methods for robust target localization by a sensor network using time differences of arrivals. IEEE Trans. on Signal Processing, 2009, 57 (7): 2775- 2784. doi: 10.1109/TSP.2009.2016891
5	WANG G, SO A M C, LI Y M Robust convex approximation methods for TDOA-based localization under NLOS conditions. IEEE Trans. on Signal Processing, 2009, 64 (13): 3281- 3296.
6	CHEN H T, WANG G, ANSARI N Improved robust TOA-based localization via NLOS balancing parameter estimation. IEEE Trans. on Vehicular Technology, 2019, 68 (6): 6177- 6181. doi: 10.1109/TVT.2019.2911187
7	LE T K, ONO N. Robust TDOA-based joint source and microphone localization in a reverberant environment using medians of acceptable recovered TOAs. Proc. of the IEEE International Workshop on Acoustic Signal Enhancement, 2016: 1−5.
8	KUHNE M, TOGNERI R, NORDHOLM S Robust source localization in reverberant environments based on weighted fuzzy clustering. IEEE Signal Processing Letters, 2009, 16 (2): 85- 88. doi: 10.1109/LSP.2008.2009833
9	ZHANG X, CUI Q, SHI Y, et al Robust localization algorithm for solving neighbor position ambiguity. Electronics Letters, 2013, 49 (17): 1106- 1107. doi: 10.1049/el.2013.1729
10	HO K C, LU X, KOVAVISARUCH L Source localization using TDOA and FDOA measurements in the presence of receiver location errors: analysis and solution. IEEE Trans. on Signal Processing, 2007, 55 (2): 684- 696. doi: 10.1109/TSP.2006.885744
11	ZAEEMZADEH, JONEIDI M, SHAHRASBI B, et al. Robust target localization based on squared range iterative reweighted least squares. Proc. of the IEEE 14th International Conference on Mobile Ad Hoc and Sensor Systems, 2017: 380−388.
12	YOUN W, HUANG Y L, MYUNG H Outlier-robust student’s-t-based IMM-VB localization for manned aircraft using TDOA measurements. IEEE/ASME Trans. on Mechatronics, 2020, 25 (3): 1646- 1658. doi: 10.1109/TMECH.2020.2982009
13	QIAO T, REDFIELD S, ABBASI A, et al Robust coarse position estimation for TDOA localization. IEEE Wireless Communication Letters, 2013, 12 (6): 623- 626.
14	HU Y C, LEUS G Robust differential received signal strength-based localization. IEEE Trans. on Signal Processing, 2017, 65 (12): 3261- 3276. doi: 10.1109/TSP.2017.2684741
15	GAO S C, ZHANG S J, WANG G, et al Robust second-order cone relaxation for TW-TOA-based localization with clock imperfection. IEEE Signal Processing Letters, 2016, 23 (8): 1047- 1051. doi: 10.1109/LSP.2016.2580743
16	HUBER P J. Robust statistics. New York: Springer, 2011.

$\delta $	Classical solution/km	Solution based on HL/km	Solution based on RHL/km
1	3.14	2.83	192.42
2		2.86	164.94
5		2.99	108.14
8		3.01	69.97
10		3.11	46.11
20		3.14	14.35
30		3.14	3.16
50		3.14	3.14
100		3.14	3.14
200		3.14	3.14

$\delta $	Classical solution/km	Solution based on HL/km	Solution based on RHL/km
1	20.37	18.28	209.79
2		18.16	171.30
5		18.23	119.24
8		18.48	94.47
10		18.35	67.29
20		18.82	35.98
30		19.24	18.37
50		19.80	20.21
100		20.37	19.98
200		20.37	20.37

$\delta $	Classical solution/km	Solution based on HL/km	Solution based on RHL/km
1	89.45	55.79	221.12
2		55.80	199.52
5		55.84	121.25
8		55.84	87.37
10		55.89	66.15
20		56.16	25.56
30		56.16	8.24
50		56.26	2.07
100		56.94	3.33
200		60.86	23.30

A robust TDOA based solution for source location using mixed Huber loss

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 9

参考文献 16

相关文章 0

编辑推荐

Metrics

本文评价