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Evaluating compressive sensing algorithms in through-the-wall radar via F1-score

机译:通过F1分数评估通过墙壁雷达的压缩传感算法

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摘要

To achieve high resolution through-the-wall radar imaging (TWRI), long wideband antenna arrays need to be considered, thus resulting in massive amounts of data. Compressive sensing (CS) techniques resolve this issue by allowing image reconstruction using much fewer measurements. The performance of different CS algorithms, when applied to TWRI, has not been investigated in a comprehensive and comparative manner. In this paper, popular CS algorithms are evaluated, to see which are most suitable for TWRI applications. As for the evaluation criteria, the notion of F_(1)-score is adopted and used in the context of TWRI; thus emphasising the algorithms ability to reconstruct an image with correctly detected targets. Algorithms responses to different levels of signal-to-noise ratio (SNR) and compression rate are evaluated. Numerical results show that for systems with low SNR, alternating direction based algorithms work better than others. When the SNR is high, algorithms depending on spectral gradient-projection methods give good results even with high compression rates.
机译:为了实现高分辨率的横壁雷达成像(TWRI),需要考虑长宽带天线阵列,从而导致大量的数据。压缩传感(CS)技术通过使用更少的测量来允许图像重建来解决此问题。应用于TWRI时,不同的CS算法的性能尚未以全面和比较的方式调查。在本文中,评估了流行的CS算法,以查看最适合于TWRI应用的算法。至于评估标准,在TWRI的背景下采用和使用F_(1)-Score的概念;从而强调能够重建具有正确检测到的目标的图像。评估对不同级别的信噪比(SNR)和压缩率的算法响应。数值结果表明,对于具有低SNR的系统,基于交替的方向的算法工作比其他算法更好。当SNR为高时,即使具有高压缩速率,取决于光谱梯度投影方法的算法即使具有高压缩速率也会产生良好的效果。

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