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On adaptive compressive sensing and radar target recognition

机译：自适应压缩感知与雷达目标识别

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摘要

Adaptive or sequential compressive sensing has received considerable attention recently. While some researchers argue that there are fundamental limits to adaptive sensing that prevents it from outperforming non-adaptive compressive sensing, others have shown that adaptive sensing of sparse signals may help speed up applications such as target detection and/or classification, and might even expedite the signal reconstruction process with less compressive measurements. This paper examines the benefits of adaptive compressive sensing of radar target backscatter with emphasis on target classification (which is accomplished using sequential hypotheses testing) and compares the results to non-adaptive compressive sensing of noisy radar signatures.
机译：自适应或顺序压缩感测近来已受到相当大的关注。尽管一些研究人员认为自适应感测存在一些基本限制，可以阻止其胜过非自适应压缩感测，但其他研究人员却表明，稀疏信号的自适应感测可以帮助加快目标检测和/或分类等应用的速度，甚至可能加速压缩量较小的信号重建过程。本文研究了雷达目标反向散射的自适应压缩感知的好处，重点是目标分类（这是通过顺序假设检验完成的），并将结果与​​嘈杂的雷达信号的非自适应压缩感知进行了比较。

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