4.7 Article

Joint Strategy of Power and Bandwidth Allocation for Multiple Maneuvering Target Tracking in Cognitive MIMO Radar With Collocated Antennas

Journal

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 72, Issue 1, Pages 190-204

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2022.3204939

Keywords

Radar tracking; Target tracking; Radar; Resource management; Bandwidth; Radar antennas; MIMO radar; Cognitive tracking; collocated MIMO radar; MMTT; PC-CRLB; resource allocation

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In this article, a joint strategy of power and bandwidth allocation (JSPBA) is proposed for multiple maneuvering target tracking (MMTT) in the multi-input multi-output (MIMO) radar with collocated antennas. The proposed algorithm optimally allocates the transmitted resources based on prior information in the closed-loop system of cognitive tracking. The nonconvex problem is solved by converting it into a series of convex problems and then formulated as standard semi-definite programming (SDP) problems for solution.
In this article, we propose a joint strategy of power and bandwidth allocation (JSPBA) for multiple maneuvering target tracking (MMTT) in the multi-input multi-output (MIMO) radar with collocated antennas. The basis of our strategy is to optimally allocate the transmitted resources of power and effective bandwidth by the prior information in the closed-loop system of cognitive tracking. On account of the predicted conditional Cramer-Rao lower bound (PC-CRLB) offering a more accurate and time-sensitive lower bound than the standard posterior CRLB (PCRLB), the PC-CRLB of the range, Doppler frequency, and direction-of-arrival (DOA) is derived, normalized and adopted as the optimization criterion. Moreover, in order to solve the nonconvex problem, the initial nonconvex problem is converted into a series of convex problems, which are further formulated as the standard semi-definite programming (SDP) problems and then be solved, by introducing the convex relaxation technique and the two-step solution technique. Simulations confirm the superiority of the proposed JSPBA algorithm, in terms of the overall tracking accuracy in the MMTT scenario.

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