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A blind stopping condition for orthogonal matching pursuit with applications to compressive sensing radar

机译:正交匹配跟踪的盲停条件及其在压感雷达中的应用

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Orthogonal matching pursuit (OMP) is a popular greedy algorithm because of its simplicity and low computational cost. In the application of OMP, one of the most important issue is to design a stopping condition according to some prior information, such as sparsity and noise level. In this paper, we provide a blind stopping condition for OMP in the presence of Gaussian noise. We theoretically analyze the stopping condition in terms of the mutual incoherence and the minimum component signal-to-noise ratio (SNR), with which OMP can stop with correct support recovery. Different from other alternatives, the proposed stopping condition can be explicitly determined regardless of prior information. So it is much suitable for practical applications. In the application of compressive sensing pulse-Doppler radar, we further analyze the support recovery performance of the proposed condition. By separately recovering the targets belonging to different Doppler frequencies, we remarkably reduce the requirement on the minimum component SNR of all targets, and thus our stopping condition is applicable to low SNR scenes. Numerical results illustrate that the proposed condition has comparable performance to the alternative with a priori information. (C) 2019 Elsevier B.V. All rights reserved.
机译:正交匹配追踪(OMP)由于其简单性和较低的计算成本而成为一种流行的贪婪算法。在OMP的应用中,最重要的问题之一是根据稀疏性和噪声水平等先验信息设计停止条件。在本文中,我们为存在高斯噪声的OMP提供了一个盲目停止条件。我们从互不相干和最小分量信噪比(SNR)的角度,从理论上分析了停止条件,通过这种方法,OMP可以通过正确的支撑恢复而停止。与其他选择不同,可以在不考虑先验信息的情况下明确确定建议的停车条件。因此非常适合实际应用。在压缩传感脉冲多普勒雷达的应用中,我们进一步分析了所提出条件的支持恢复性能。通过分别恢复属于不同多普勒频率的目标,我们显着降低了对所有目标的最小分量SNR的要求,因此我们的停止条件适用于低SNR场景。数值结果表明,提出的条件与具有先验信息的替代方法具有可比的性能。 (C)2019 Elsevier B.V.保留所有权利。

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