Learning-based sparse array optimization for dual function radar-communication system

Rui Wang; Feng Xi; Shengyao Chen

doi:10.1117/12.3022771

28 March 2024 Learning-based sparse array optimization for dual function radar-communication system

Rui Wang, Feng Xi, Shengyao Chen

Proceedings Volume 13091, Fifteenth International Conference on Signal Processing Systems (ICSPS 2023); 130911B (2024) https://doi.org/10.1117/12.3022771
Event: Fifteenth International Conference on Signal Processing Systems (ICSPS 2023), 2023, Xi’an, China

Abstract

This paper considers a multi-input multi-output (MIMO) dual functional radar communication (DFRC) system and focuses on the joint design of transmit beamforming matrix and sparse antenna array. We propose to minimize the Cramér-Rao bound (CRB) of radar sensing while preserving a predetermined level of signal-to-interference-plus-noise ratio (SINR) for the communication users. The hybrid analog-digital (HAD) beamforming technology with fewer radiofrequency (RF) chains is considered to reduce the cost of hardware system as well as to deal with the rank-deficient problem of radar sensing. Due to the complex representation of the CRB matrix, the learning-based method is proposed to simultaneously optimize the HAD beamforming matrix and antenna selection matrix. Numerical simulations are conducted to demonstrate the effectiveness of the proposed method.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Rui Wang, Feng Xi, and Shengyao Chen "Learning-based sparse array optimization for dual function radar-communication system", Proc. SPIE 13091, Fifteenth International Conference on Signal Processing Systems (ICSPS 2023), 130911B (28 March 2024); https://doi.org/10.1117/12.3022771

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