Cramer-Rao Bound Analysis and Beamforming Design for Integrated Sensing and Communication With Extended Targets

被引:1
作者
Wang, Yiqiu [1 ,2 ]
Tao, Meixia [1 ,2 ]
Sun, Shu [1 ,2 ]
机构
[1] Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200240, Peoples R China
[2] Shanghai Jiao Tong Univ, Cooperat Medianet Innovat Ctr CMIC, Shanghai 200240, Peoples R China
关键词
Radar; Array signal processing; Integrated sensing and communication; Estimation; Optimization; Copper; Wireless communication; Cram & eacute; r-Rao bound; transmit beamforming design; semidefinite relaxation; zero-forcing; FUNCTION RADAR-COMMUNICATIONS; JOINT RADAR; MIMO RADAR; OPTIMIZATION; SYSTEMS;
D O I
10.1109/TWC.2024.3435864
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper studies an integrated sensing and communication (ISAC) system, where a multi-antenna base station transmits beamformed signals for joint downlink multi-user communication and radar sensing of an extended target (ET). By considering echo signals as reflections from valid elements on the ET contour, a set of novel Cramer-Rao bounds (CRBs) is derived for parameter estimation of the ET, including central range, direction, and orientation. The ISAC transmit beamforming design is then formulated as an optimization problem, aiming to minimize the CRB associated with radar sensing, while satisfying a minimum signal-to-interference-pulse-noise ratio requirement for each communication user, along with a 3-dB beam coverage constraint tailored for the ET. To solve this non-convex problem, we utilize semidefinite relaxation (SDR) and propose a rank-one solution extraction scheme for non-tight relaxation circumstances. To reduce the computation complexity, we further employ an efficient zero-forcing (ZF) based beamforming design, where the sensing task is performed in the null space of communication channels. Numerical results validate the effectiveness of the obtained CRB, revealing the diverse features of CRB for differently shaped ETs. The proposed SDR beamforming design outperforms benchmark designs with lower estimation error and CRB, while the ZF beamforming design greatly improves computation efficiency with minor sensing performance loss.
引用
收藏
页码:15987 / 16000
页数:14
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