论文标题
多IR辅助雷达中的关节波形和无源波束形式设计
Joint Waveform and Passive Beamformer Design in Multi-IRS-Aided Radar
论文作者
论文摘要
智能反射表面（IRS）技术最近引起了人们对非远处雷达遥感的重大兴趣。先前的作品主要集中在为此问题设计单个IRS波束形式。本文在文献中首次考虑了多IR的多输入多输出（MIMO）雷达，并共同设计了传输的单型波形和最佳IRS束光束器。为此，我们将目标方向（DOA）的Cramer-Rao下限（CRLB）作为性能度量指标。从硬件角度来看，单模型的发送序列是首选波形。我们表明，通过合适的转换，可以将联合设计问题重新归类为两个单模型二次程序（UQP）。为了应对两种UQP的NP固定性质，我们提出了使用低成本方法样迭代的多IRS雷达（UBER）算法的单模型波形和横梁形成设计。数值实验表明，从我们的Uber算法获得的MIMO波形和相移可有效改善DOA估计的CRLB。
Intelligent reflecting surface (IRS) technology has recently attracted a significant interest in non-light-of-sight radar remote sensing. Prior works have largely focused on designing single IRS beamformers for this problem. For the first time in the literature, this paper considers multi-IRS-aided multiple-input multiple-output (MIMO) radar and jointly designs the transmit unimodular waveforms and optimal IRS beamformers. To this end, we derive the Cramer-Rao lower bound (CRLB) of target direction-of-arrival (DoA) as a performance metric. Unimodular transmit sequences are the preferred waveforms from a hardware perspective. We show that, through suitable transformations, the joint design problem can be reformulated as two unimodular quadratic programs (UQP). To deal with the NP-hard nature of both UQPs, we propose unimodular waveform and beamforming design for multi-IRS radar (UBeR) algorithm that takes advantage of the low-cost power method-like iterations. Numerical experiments illustrate that the MIMO waveforms and phase shifts obtained from our UBeR algorithm are effective in improving the CRLB of DoA estimation.
