Enhanced Angle-Range Cluster Parameter Estimation in Full-Duplex ISAC Systems

This work studies an integrated sensing and communication (ISAC) framework for targets that are spread both in the angle and range domains. We model each target using a cluster of rays parameterized by a specific density function, and propose a truncated Multiple Signal Classification (MUSIC) spread (TMS) algorithm to accurately estimate the parameters of the density function. Unlike the conventional MUSIC spread (CMS), TMS restricts the signal subspace rank based on the eigen decomposition of the received-signal autocorrelation. We also propose a discrete Fourier transform (DFT) based algorithm for estimating the distance and range spread of each target. Leveraging these estimates, we then develop a dynamic transmit beamforming algorithm that successfully illuminates multiple targets while also serving multiple downlink (DL) users. Simulation results demonstrate the superiority of our proposed algorithms over baseline schemes in both low and high signal-to-noise ratio (SNR) regimes as well as under a wide angular spread regime.