In this paper, we design the wideband hybrid-analog-digital (HAD) beamforming for integrated sensing and communication (ISAC) systems. Specifically, we incorporate the phase shifters (PSs) and true-time delay lines (TTDs) to combat the wideband beam squint effect, which are able to provide frequency-dependent phase shift in the analog beamforming stage. The fully-digital (FD) beamformers with guaranteed sensing and communication signal-to-interference-plus-noise ratios (SINRs) are first designed. Then, the HAD beamforming is formulated as a least squares (LS) problem to approximate the designed FD beamformers with constant-modulus constraints, whose main challenges are the complicated objective function and the non-convex constraints. To tackle these issues, we majorize the objective function to decouple the optimization variables. Then, the beamformer for PSs can be solved with a closed-form solution, whereas the beamformer for TTDs can be obtained by a simple grid-search. Finally, we adjust the PS and TTD beamformers by the Riemannian conjugate gradient method (RCGM) to improve the performance. Simulation results demonstrate the superior performance of the proposed algorithm over the conventional algorithm.

In this paper, we consider the moving target sensing problem for integrated sensing and communication (ISAC) sys-tems in clutter environment. Scatterers produce strong clutter, deteriorating the performance of ISAC systems in practice. Given that scatterers are typically stationary and the targets of interest are usually moving, we here focus on sensing the moving targets. Specifically, we adopt a scanning beam to search for moving target candidates. For the received signal in each scan, we employ high-pass filtering in the Doppler domain to suppress the clutter within the echo, thereby identifying candidate moving targets according to the power of filtered signal. Then, we adopt root-MUSIC-based algorithms to estimate the angle, range, and radial velocity of these candidate moving targets. Subsequently, we propose a target detection algorithm to reject false targets. Simulation results validate the effectiveness of these proposed methods.

In this paper, we propose a practical integrated sensing and communications (ISAC) framework to sense dynamic targets from clutter environment while ensuring users communications quality. To implement communications function and sensing function simultaneously, we design multiple communications beams that can communicate with the users as well as one sensing beam that can rotate and scan the entire space. To minimize the interference of sensing beam on existing communications systems, we divide the service area intosensing beam for sensing (S4S) sectorandcommunications beam for sensing (C4S) sector, and provide beamforming design and power allocation optimization strategies for each type sector. Unlike most existing ISAC studies that ignore the interference of static environmental clutter on target sensing, we construct a mixed sensing channel model that includes both static environment and dynamic targets. When base station receives the echo signals, it first filters out the interference from static environmental clutter and extracts the effective dynamic target echoes. Then a complete and practical dynamic target sensing scheme is designed to detect the presence of dynamic targets and to estimate their angles, distances, and velocities. In particular, dynamic target detection and angle estimation are realized through angle-Doppler spectrum estimation (ADSE) and joint detection over multiple subcarriers (MSJD), while distance and velocity estimation are realized through the extended subspace algorithm. Simulation results demonstrate the effectiveness of the proposed scheme and its superiority over the existing methods that ignore environmental clutter.

Intelligent reflecting surface (IRS) has recently gained significant academic interest as a prospective contender for improving wireless communication system coverage and spectral efficiency. This paper investigates a robust beamforming design of an IRS-aided dual-functional radar-communication (DFRC) system in the presence of channel uncertainty, as opposed to the idealistic assumption of perfect channel state information (CSI) in the existing literature. The optimization is carried out by minimizing the transmit power while ensuring the detection performance and the achievable rate of the user meets the quality of service (QoS) requirement, which turns out to be a non-convex and intractable problem. To circumvent this issue, we alternatively update the transmit beamforming vector and the phase shifts at the IRS using the block coordinate descent (BCD) algorithm. Afterwards, the resulting two sub-problems can be efficiently solved with the help of approximation and transformation techniques. Simulation results have validated the convergence and effectiveness of the proposed algorithm.