基于块cs的分布式MIMO系统参数估计的能量分配

A. Abtahi, M. Modarres-Hashemi, F. Marvasti, F. Tabataba
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引用次数: 5

摘要

利用MIMO雷达中的压缩感知(CS)技术,可以消除对高速率A/D转换器的需求,并大大减少发送到融合中心的采样量。在分布式MIMO雷达中,接收到的信号可以被建模为一个基的块稀疏信号。因此,可以使用块CS方法代替经典CS方法来实现更精确的目标参数估计。本文提出了一种新的发射机能量分配方法,以提高基于分块cs的分布式MIMO雷达的性能。该方法基于传感矩阵块相干性上界的最小化。仿真结果表明,该方法显著提高了多目标参数估计的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy allocation for parameter estimation in block CS-based distributed MIMO systems
Exploiting Compressive Sensing (CS) in MIMO radars, we can remove the need of the high rate A/D converters and send much less samples to the fusion center. In distributed MIMO radars, the received signal can be modeled as a block sparse signal in a basis. Thus, block CS methods can be used instead of classical CS ones to achieve more accurate target parameter estimation. In this paper a new method of energy allocation to the transmitters is proposed to improve the performance of the block CS-based distributed MIMO radars. This method is based on the minimization of an upper bound of the sensing matrix block-coherence. Simulation results show a significant increase in the accuracy of multiple targets parameter estimation.
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