论文标题
压缩域检测和估计的估计
Compressed-Domain Detection and Estimation for Colocated MIMO Radar
论文作者
论文摘要
本文提出了压缩域信号处理（CSP）多个输入多重输出（MIMO）雷达，这是一种MIMO雷达方法，通过利用CSP的想法来实现大量样品复杂性的降低。 CSP MIMO雷达涉及两个级别的数据压缩，然后在压缩域中检测目标检测。首先，在接收天线上使用压缩感应，然后是capon束光束器，旨在抑制混乱。利用波束形式输出的稀疏性质，将第二个压缩应用于过滤数据。随后通过在离散角空间的每个网格点制定和解决假设测试问题来进行目标检测。与常规压缩感（CS）MIMO雷达相比，提出的方法可以使某些设置中样品复杂性的8倍降低，从而实现了更快的目标检测。提供了拟议检测器的接收器操作特性（ROC）曲线。仿真结果表明，所提出的方法的表现优于基于恢复的压缩传感算法。
This paper proposes compressed domain signal processing (CSP) multiple input multiple output (MIMO) radar, a MIMO radar approach that achieves substantial sample complexity reduction by exploiting the idea of CSP. CSP MIMO radar involves two levels of data compression followed by target detection at the compressed domain. First, compressive sensing is applied at the receive antennas, followed by a Capon beamformer which is designed to suppress clutter. Exploiting the sparse nature of the beamformer output, a second compression is applied to the filtered data. Target detection is subsequently conducted by formulating and solving a hypothesis testing problem at each grid point of the discretized angle space. The proposed approach enables an 8-fold reduction of the sample complexity in some settings as compared to a conventional compressed sensing (CS) MIMO radar thus enabling faster target detection. Receiver operating characteristic (ROC) curves of the proposed detector are provided. Simulation results show that the proposed approach outperforms recovery-based compressed sensing algorithms.
