Cramér-Rao Bound Optimization for Joint Radar-Communication Beamforming

In this paper, we propose multi-input multi-output (MIMO) beamforming designs towards joint radar sensing and multi-user communications. We employ the Cramér-Rao bound (CRB) as a performance metric of target estimation, under both point and extended target scenarios. We then propose minimizing the C...

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Vydáno v:IEEE transactions on signal processing Ročník 70; s. 240 - 253
Hlavní autoři: Liu, Fan, Liu, Ya-Feng, Li, Ang, Masouros, Christos, Eldar, Yonina C.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Array signal processing
Beamforming
Cramér-Rao bound
Dual-functional radar-communication
Estimation
joint beamforming
Optimization
Radar
Radar antennas
Receiving antennas
Semidefinite programming
semidefinite relaxation
Sensors
successive convex approximation
ISSN:1053-587X, 1941-0476
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Shrnutí:In this paper, we propose multi-input multi-output (MIMO) beamforming designs towards joint radar sensing and multi-user communications. We employ the Cramér-Rao bound (CRB) as a performance metric of target estimation, under both point and extended target scenarios. We then propose minimizing the CRB of radar sensing while guaranteeing a pre-defined level of signal-to-interference-plus-noise ratio (SINR) for each communication user. For the single-user scenario, we derive a closed form for the optimal solution for both cases of point and extended targets. For the multi-user scenario, we show that both problems can be relaxed into semidefinite programming by using the semidefinite relaxation approach, and prove that the global optimum can be generally obtained. Finally, we demonstrate numerically that the globally optimal solutions are reachable via the proposed methods, which provide significant gains in target estimation performance over state-of-the-art benchmarks.
Bibliografie:ObjectType-Article-1
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ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2021.3135692