Cooperative Detection for mmWave Radar-Communication Systems

Abstract

Spectral co-existence of radar and communication (RadCom) systems causes mutual interference between the two systems, compromising both the data exchange and radar sensing capabilities. Focusing on the radars' detection performance, in this paper, we propose a novel cooperative detection technique in the context of millimeter-wave (mmWave) RadCom systems, under a constant false alarm constraint. Existing detection techniques assign a single base station (BS) operating in radar mode (RM) for the detection of a target. In contrast, our proposed technique performs joint target detection through multiple cooperative RMenabled BSs (RBSs). Specifically, our proposed technique exploits the fusion of individual sensing information by a set of preselected cooperative RBSs, aiming at enhancing the detection performance. We consider three pre-selection policies based on: 1) the Euclidean distance, 2) the received signal power, and 3) a random selection. In addition, for the fusion of the sensing information, we consider three hard-decision combining rules, namely OR, Majority and AND rule. By using stochastic geometry tools, analytical expressions for the detection performance are expressed for each pre-selection policy and combining rule. Our results reveal that the proposed technique significantly improves the detection performance of the mmWave RadCom systems.

Recursive spatial-temporal clustering-based target detection with millimeter-wave radar point cloud

“…Traditional target detection methods exploit spatial domain clustering algorithms to identify TPs and NPs in a radar point cloud based on the spatial Euclidean distance or its variants [19]. To classify fall, sit, and walk motions of two persons, the GMM is employed in [20] for target detection with mmWave radar point cloud as a preprocessing step.…”