Clutter Suppression based Sensing Algorithm in ISAC System

Integrated sensing and communication (ISAC) is envisioned as a novel feature in the forthcoming sixth-generation (6G) wireless communication. Estimation of the location and velocity of the target is the fundamental task of the sensing network. However, the echos from the targets are always very weak and their location and velocity are difficult to estimate by the sensing node, especially when there is some clutter to interfere the echo. In this paper, we investigate a clutter suppression-based sensing algorithm to estimate the location and velocity of the target. The proposed algorithm is based on the clutter suppression operation with orthogonal frequency division multiplexing (OFDM) waveform signal model, including the clutter suppression-based two-dimensional inverse fast Fourier transform (CS-2D-IFFT) for distance and velocity estimation, and the clutter suppression-based two-dimensional multiple signal classification (CS-2D-MUSIC) for angle of arrival (AoA) estimation. The evaluation results show that the proposed algorithm can effectively eliminate the effects of clutter and reduce the probability that recognizing a clutter as a target.