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Compressed-Domain Detection and Estimation for Colocated MIMO Radar

机译:COLOCATED MIMO雷达的压缩域检测和估计

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摘要

This article proposes a 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 eightfold 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 curves of the proposed detector are provided. Simulation results show that the proposed approach outperforms recovery-based CS algorithms.
机译:本文提出了一种压缩域信号处理(CSP)多输入多输出(MIMO)雷达,一种MIMO雷达方法,通过利用CSP的思想来实现大量的样本复杂性。 CSP MIMO雷达涉及两级数据压缩,然后在压缩域处进行目标检测。首先,在接收天线上施加压缩感测,然后施加Capon波束形成器,其被设计为抑制杂波。利用波束形成器输出的稀疏性质,将第二个压缩应用于过滤的数据。随后通过在离散角度空间的每个网格点中配制和解决假设检测问题,随后进行目标检测。与传统的压缩感测(CS)MIMO雷达相比,所提出的方法能够在某些设置中在某些设置中减少样本复杂性,从而实现更快的目标检测。提供了所提出的检测器的接收器操作特性曲线。仿真结果表明,所提出的方法优于基于恢复的CS算法。

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