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Analysis and design of algorithms for compressive sensing based noise radar systems

机译:基于压缩感知的噪声雷达系统算法分析与设计

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We study the compressive radar imaging problem from the perspective of statistical estimation. The goal of this paper is to characterize the estimation error. Conventional radar estimation and detection techniques are characterized by concrete performance guarantees which relate directly to practical systems. The state evolution approach applied to compressive sensing is particularly useful for such analysis. We emphasize the importance of the uniform norm of the estimation error for radar imaging. In the second part of the paper, we propose a weighted compressive sampling scheme for noise radar imaging that utilizes prior information about the target scene. The weights are obtained using the mutual information estimation between target echoes and the transmitted signals with an energy constraint.
机译:我们从统计估计的角度研究压缩雷达成像问题。本文的目的是表征估计误差。常规雷达估计和检测技术的特征在于与实际系统直接相关的具体性能保证。应用于压缩感测的状态演化方法对于此类分析特别有用。我们强调雷达成像估计误差的统一范数的重要性。在本文的第二部分中,我们提出了一种噪声雷达成像的加权压缩采样方案,该方案利用了有关目标场景的先验信息。使用目标回波和具有能量约束的发射信号之间的互信息估计来获得权重。

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