Resource Scheduling Base on Bayesian Cramer-Rao Lower Bound for Multi-Target Tracking in Netted Colocated MIMO Radar Systems

Sijian Liao, Zhihong Peng, Junqi Cai

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

In this paper, an effective joint beam selection and power allocation (JBSPA) method is proposed to solve the online resource scheduling problem for multi-target tracking in distributed MIMO radar system. Overall target tracking performance can be improved by optimizing radar system beam selection and power allocation, since each MIMO radar can generate a time-varying beam, and adjust the quality of the observed signal by controlling the transmit power of each beam. In our method the feedback information of the target tracking period is used to complete the optimal radar-targets assignment and power allocation, the objective function is formulated based on the Bayesian Cramér-Rao lower bound, as the formulated JBSPA problem is non-convex, a three steps solution method based on reward matrix is proposed to solve it effectively. Numerical results show that the proposed JBSPA method can deliver better performance than the competitors in overall MTT performance.

源语言英语
主期刊名Proceedings of the 40th Chinese Control Conference, CCC 2021
编辑Chen Peng, Jian Sun
出版商IEEE Computer Society
1791-1796
页数6
ISBN(电子版)9789881563804
DOI
出版状态已出版 - 26 7月 2021
活动40th Chinese Control Conference, CCC 2021 - Shanghai, 中国
期限: 26 7月 202128 7月 2021

出版系列

姓名Chinese Control Conference, CCC
2021-July
ISSN(印刷版)1934-1768
ISSN(电子版)2161-2927

会议

会议40th Chinese Control Conference, CCC 2021
国家/地区中国
Shanghai
时期26/07/2128/07/21

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