Finite sensor selection algorithm in distributed MIMO radar for joint target tracking and detection

doi:10.23919/JSEE.2020.000007

Journal of Systems Engineering and Electronics ›› 2020, Vol. 31 ›› Issue (2): 290-302.doi: 10.23919/JSEE.2020.000007

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Finite sensor selection algorithm in distributed MIMO radar for joint target tracking and detection

Haowei ZHANG^1,*(), Junwei XIE¹(), Jiaang GE¹(), Zhaojian ZHANG²(), Wenlong LU³()

¹ Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China
² Air Force Early Warning Academy of the PLA, Wuhan 410039, China
³ Unit 95899 of the PLA, Beijing 100085, China

Received:2019-01-01 Online:2020-04-30 Published:2020-04-30
Contact: Haowei ZHANG E-mail:zhw_xhzf@163.com;xjw_xjw_123@163.com;752858328@qq.com;zzj554038@163.com;youranqixia521@126.com
About author:ZHANG Haowei was born in 1992. He received his bachelor and master degrees from the Air and Missile Defense College, Air Force Engineering University, Xi'an, Shaanxi, China, in 2014 and 2016, respectively. He is currently pursuing his Ph.D. degree in the Air and Missile Defense College. His research interests include multifunction radar resource management and intelligent scheduling. E-mail: zhw_xhzf@163.com|XIE Junwei was born in 1970. He received his bachelor, master, and doctor degrees from the Air and Missile Defense College, Air Force Engineering University, Xi'an, Shaanxi, China in 1993, 1996 and 2009, respectively. He is currently a professor in the Air and Missile Defense College. His research interests include novel radar systems as well as jamming and anti-jamming. He has published more than 100 refereed journal articles, book chapters, and conference papers. E-mail: xjw_xjw_123@163.com|GE Jiaang was born in 1995. He received his bache-linebreak lor degree from Beijing University of Aeronautics and Astronautics, Beijing, China, in 2017. He is currently pursuing his Ph.D. degree in the Air and Missile Defense College. His research interest is radar signal processing. E-mail: 752858328@qq.com|ZHANG Zhaojian was born in 1989. He received his bachelor, master and doctor degrees from the Air and Missile Defense College, the Air Force Engineering University, Xi'an, Shaanxi, China in 2011, 2013 and 2017 respectively. He is currently a lecturer in the Air Force Early Warning Academy of the PLA, Hubei, Wuhan. His research interest is radar signal processing. E-mail: zzj554038@163.com|LU Wenlong was born in 1988. He received his bachelor, master and doctor degrees from the Air and Missile Defense College, Air Force Engineering University, Xi'an, Shaanxi, China in 2010, 2012 and 2016 respectively. He is currently an engineer in Unit 95899 of the PLA. His research interest is time and frequency analysis. E-mail: youranqixia521@126.com
Supported by:
the National Natural Science Foundation of China(61601504);This work was supported by the National Natural Science Foundation of China (61601504)

Abstract

Abstract:

Due to the requirement of anti-interception and the limitation of processing capability of the fusion center, the subarray selection is very important for the distributed multiple-input multiple-output (MIMO) radar system, especially in the hostile environment. In such conditions, an efficient subarray selection strategy is proposed for MIMO radar performing tasks of target tracking and detection. The goal of the proposed strategy is to minimize the worst-case predicted posterior Cramer-Rao lower bound (PCRLB) while maximizing the detection probability for a certain region. It is shown that the subarray selection problem is NP-hard, and a modified particle swarm optimization (MPSO) algorithm is developed as the solution strategy. A large number of simulations verify that the MPSO can provide close performance to the exhaustive search (ES) algorithm. Furthermore, the MPSO has the advantages of simpler structure and lower computational complexity than the multi-start local search algorithm.

Key words: distributed multiple-input multiple-output (MIMO) radar, subarray selection, target tracking, target detection, particle swarm optimization (PSO).

Haowei ZHANG, Junwei XIE, Jiaang GE, Zhaojian ZHANG, Wenlong LU. Finite sensor selection algorithm in distributed MIMO radar for joint target tracking and detection[J]. Journal of Systems Engineering and Electronics, 2020, 31(2): 290-302.

Figures/Tables 11

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References 35

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Algorithm	ES	MSLS	MPSO
Computational complexity	$O(2^{M + N})$	$O(KMN(M+N))$	$O(N_{\rm{pop}}t_{\max})$

Frame	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16
MPSO	0	0	0	0	1.25	0	0	0	0	0.82	0	0	1.35	0	0	0
MSLS	0	0	0	0	1.33	0.91	0	1.06	0	0.54	0	0	2.60	0	3.67	4.08
PSO	0	8.44	3.74	5.35	6.05	7.32	5.94	10.17	8.04	6.63	6.42	5.61	4.64	14.58	12.09	13.46

$K$	4	6	8	10	12	14	16
ES	4 425	38 340	125 880	184 754	125 970	38 760	4 845
MSLS	3 500	6 600	9 300	11 600	13 500	15 000	16 100
MPSO	2 500	2 500	5 000	5 000	5 000	2 500	2 500
PSO	2 500	2 500	5 000	5 000	5 000	2 500	2 500

Frame	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16
MPSO	0	1.34	0.81	0.32	0.44	1.12	0.34	1.81	1.24	0.31	0.96	1.18	0.31	0.97	0.43	0.65
MSLS	0	0.94	0.96	0.48	0.55	0.91	0.88	2.08	1.19	1.44	0.88	1.43	0.56	0.86	0.84	1.88
PSO	4.52	10.23	8.64	7.46	9.27	7.35	8.31	18.68	10.44	12.63	7.82	5.45	8.36	12.48	19.38	25.46

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Finite sensor selection algorithm in distributed MIMO radar for joint target tracking and detection

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