Full Duplex ISAC with Cluster Ray Targets: Parameter Estimation and Beamforming

Abstract

This work studies a full-duplex integrated sensing and communication (ISAC) resolution framework for spatially distributed systems. Conventional high-resolution methods, such as MUSIC, fail to localize distributed targets because the signal subspace is full rank, even in the single-distributed-target setting. In an effort to resolve this, we propose a two-stage estimator, which successfully resolve multiple distributed targets and outperforms several baseline schemes without incurring any additional computational complexity. Our first-stage estimator uses the Fast Fourier transform to estimate the coarse spectrum, while in the second stage, we apply the Gauss-Newton method to fine-tune the angular estimates. Apart from this, we also propose an optimization framework for designing an adaptive beamformer capable of synthesizing both wide and directed beams to cover the full extent of the targets while also fulfilling data rate requirements of multiple users. The beamformer also meets the data-rate requirements of multiple users, maintaining quality of service. Simulation results demonstrate a threefold improvement in spread estimation under low signal-to-noise ratio (SNR) conditions and a twofold improvement for low-spread targets.