Adaptive time-space resource and waveform control for collocated MIMO radar with simultaneous multi-beam

doi:10.23919/JSEE.2022.000006

Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (1): 47-59.doi: 10.23919/JSEE.2022.000006

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Adaptive time-space resource and waveform control for collocated MIMO radar with simultaneous multi-beam

Ting CHENG*(), Xi LI(), Qianqian TAN(), Yang SU()

¹ School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

Received:2020-12-14 Accepted:2021-12-13 Online:2022-01-18 Published:2022-02-22
Contact: Ting CHENG E-mail:citrus@uestc.edu.cn;779617448@qq.com;2210359327@qq.com;yangsu_ee@163.com
About author:|CHENG Ting was born in 1982. She received her Ph.D. degree in signal and information processing from University of Electronic Science and Technology of China (UESTC) in 2008. From November 2013 to November 2014, she was a visiting scholar in the Department of Electronic Engineering of the University of New Orleans, Louisiana, US. She is an associate professor in the School of Information and Communication Engineering, UESTC. Her research interests include target tracking, radar resource management, and data fusion. E-mail: citrus@uestc.edu.cn||LI Xi was born in 1995. She received her M.S. degree in electronic and communication engineering in 2021 from University of Electronic Science and Technology of China. Her research interests are target tracking as well as radar resource management. E-mail: 779617448@qq.com||TAN Qianqian was born in 1995. She received her M.S. degree in signal and information processing in 2021 from University of Electronic Science and Technology of China. Her research interests is intelligent scheduling. E-mail: 2210359327@qq.com||SU Yang was born in 1995. He received his M.S. degree in signal and information processing in 2019 from University of Electronic Science and Technology of China, where he is currently working toward his Ph.D. degree in signal and information processing. His research interests include target tracking and MIMO radar research management. E-mail: yangsu_ee@163.com
Supported by:
This work was supported by the National Natural Science Foundation of China (61671137)

Abstract

Abstract:

Collocated multiple input multiple output (MIMO) radar, which has agile multi-beam working mode, can offer enhanced multiple targets tracking (MTT) ability. In detail, it can illuminate different targets simultaneously with multi-beam or one wide beam among multi-beam, providing greater degree of freedom in system resource control. An adaptive time-space resource and waveform control optimization model for the collocated MIMO radar with simultaneous multi-beam is proposed in this paper. The aim of the proposed scheme is to improve the overall tracking accuracy and meanwhile minimize the resource consumption under the guarantee of effective targets detection. A resource and waveform control algorithm which integrates the genetic algorithm (GA) is proposed to solve the optimization problem. The optimal transmitting waveform parameters, system sampling period, sub-array number, binary radar tracking parameter $ \chi _i\left( {{t_k}} \right) $ , transmitting energy and multi-beam direction vector combination are chosen adaptively, where the first one realizes the waveform control and the latter five realize the time-space resource allocation. Simulation results demonstrate the effectiveness of the proposed control method.

Key words: multiple targets tracking (MTT), collocated multiple input multiple output (MIMO) radar, time-space resource allocation, waveform control

Ting CHENG, Xi LI, Qianqian TAN, Yang SU. Adaptive time-space resource and waveform control for collocated MIMO radar with simultaneous multi-beam[J]. Journal of Systems Engineering and Electronics, 2022, 33(1): 47-59.

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Target	Duration time/s	Initial location/km	Initial velocity/ (m·s^?1)
Target 1	0?100	(120, 120.4)	(20,6)
Target 2	20?100	(120.8, 120.8)	(15,0)
Target 3	20?100	(121, 120)	(15,12)

Working mode	Specific meaning
$q = 1$	Update Target 1
$q = 2$	Update Target 2
$q = 3$	Update Target 3
$q = 4$	Update Targets 1, 2
$q = 5$	Update Targets 1, 3
$q = 6$	Update Targets 2, 3
$q = 7$	Update Targets 1, 2, 3

Algorithm	$\bar C$	$\eta $ /%
Proposed algorithm	0.0967	?
Algorithm 1	0.110 5	14.27
Algorithm 2	0.122 7	26.88
Algorithm 3	0.118 0	22.03
Algorithm 4	0.124 9	29.16
Algorithm 5	0.129 6	34.02
Algorithm 6	0.1898	96.28

Adaptive time-space resource and waveform control for collocated MIMO radar with simultaneous multi-beam

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