Blind-Zone Target Detection and Direction Estimation: An IRS-Aided Approach

Intelligent reflecting surface (IRS) has the potential of improving sensing performance, due to its capability of reshaping the echo signals. Different from the existing literature, which has commonly focused on IRS beamforming optimization, in this paper, we pay special attention to designing effective signal processing approaches to extract sensing information from IRS-reshaped echo signals. To this end, we investigate a blind-zone target detection and direction estimation problem in the IRS-aided orthogonal frequency division multiplexing dual-function radar-communication system. To solve this problem, we identify that the existence and direction of the target can be determined by processing the reshaped echo signals under varying IRS beams. Based on this identification, we propose a novel target detection and direction estimation framework, consisting of a hierarchical codebook, a delay spectrum peak (DSP)-based beam training scheme, and a beam refinement scheme. Specifically, the hierarchical codebook enables the IRS to perform three-dimensional beamforming with adjustable beam direction and width. The DSP-based beam training scheme is used to detect the existence of a target within the beam scanning coverage and obtain a rough estimated direction of the target. The beam refinement scheme is designed to further improve the accuracy of the direction estimation. Through analysis and numerical results, we demonstrate that an N-fold signal processing gain can be achieved with N sub-carriers, compared with the traditional power detector. We also show that an up to 99.7% target detection rate can be achieved with our proposed DSP-based beam training scheme. In addition, after the beam refinement, our proposed beam training scheme can achieve 10
⁻³
-rad level accuracy of direction estimation, which is two times better than that achieved by the beam training scheme without beam refinement.