Intelligent reflecting surface (IRS) is recognized as an enabler of future dual-function radar-communications (DFRC) by improving spectral efficiency, coverage, parameter estimation, and interference suppression. Prior studies on IRS-aided DFRC focus either on narrowband processing, single-IRS deployment, static targets, non-clutter scenario, or on the under-utilized line-of-sight (LoS) and non-line-of-sight (NLoS) paths. In this paper, we address the aforementioned shortcomings by optimizing a wideband DFRC system comprising multiple IRSs and a dual-function base station that jointly processes the LoS and NLoS wideband multi-carrier signals to improve both the communications SINR and the radar SINR in the presence of a moving target and clutter. We formulate the transmit, {receive} and IRS beamformer design as the maximization of the worst-case radar signal-to-interference-plus-noise ratio (SINR) subject to transmit power and communications SINR. We tackle this nonconvex problem under the alternating optimization framework, where the subproblems are solved by a combination of Dinkelbach algorithm, consensus alternating direction method of multipliers, and Riemannian steepest decent. Our numerical experiments show that the proposed multi-IRS-aided wideband DFRC provides over $4$ dB radar SINR and $31.7$\% improvement in target detection over a single-IRS system.

翻译：智能反射面被誉为未来双功能雷达通信系统的关键使能技术，可提升频谱效率、覆盖范围、参数估计性能及干扰抑制能力。现有关于智能反射面辅助双功能雷达通信的研究主要聚焦于窄带处理、单智能反射面部署、静态目标、无杂波场景，或未充分利用视距与非视距路径。本文针对上述不足，优化了一个包含多个智能反射面及双功能基站的宽带双功能雷达通信系统——该基站联合处理视距与非视距宽带多载波信号，在存在移动目标及杂波条件下同时提升通信信干噪比与雷达信干噪比。我们将发射、接收及智能反射面波束成形设计建模为在发射功率与通信信干噪比约束下最大化最差情况雷达信干噪比的优化问题。采用交替优化框架处理该非凸问题，其中子问题通过Dinkelbach算法、共识交替方向乘子法及黎曼最速下降法联合求解。数值实验表明，与单智能反射面系统相比，所提出的多智能反射面辅助宽带双功能雷达通信系统可提供超过4 dB的雷达信干噪比增益，目标检测性能提升31.7%。