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.
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