Compressed Statistical Testing and Application to Radar

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Compressed Statistical Testing and Application to Radar

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dc.contributor.author Wicks, Michael C.
dc.contributor.author Kung, H.T. T.
dc.contributor.author Chen, Hsieh-Chung
dc.date.accessioned 2012-12-06T18:31:48Z
dc.date.issued 2012-12-06
dc.identifier.citation Chen, Hsieh-Chung, H. T. Kung, and Michael Wicks. 2012. Compressed statistical testing and application to radar. Paper presented at the 1st International Workshop on Compressed Sensing Applied to Radar (CoSeRa 2012) Bonn, Germany, May 14-16, 2012. en_US
dc.identifier.uri http://nrs.harvard.edu/urn-3:HUL.InstRepos:10007899
dc.description.abstract We present compressed statistical testing (CST) with an illustrative application to radar target detection. We characterize an optimality condition for a compressed domain test to yield the same result as the corresponding test in the uncompressed domain. We demonstrate by simulation that under high SNR, a likelihood ratio test with compressed samples at 3.3x or even higher compression ratio can achieve detection performance comparable to that with uncompressed data. For example, our compressed domain Sample Matrix Inversion test for radar target detection can achieve constant false alarm rate (CFAR) performance similar to the corresponding test in the raw data domain. By exploiting signal sparsity in the target and interference returns, compressive sensing based CST can incur a much lower processing cost in statistical training and decision making, and can therefore enable a variety of distributed applications such as target detection on resource limited mobile devices. en_US
dc.description.sponsorship Engineering and Applied Sciences en_US
dc.language.iso en_US en_US
dc.relation.hasversion http://www.eecs.harvard.edu/~htk/publication/2012-cosera-chen-kung-wicks.pdf en_US
dash.license LAA
dc.subject compressed statistical testing en_US
dc.subject likelihood ratio test en_US
dc.subject sample matrix inversion en_US
dc.subject pulse-Doppler radar en_US
dc.subject target detection en_US
dc.subject space-time adaptive processing en_US
dc.subject compressive sensing en_US
dc.subject compressed sampling en_US
dc.subject compressed domain processing en_US
dc.title Compressed Statistical Testing and Application to Radar en_US
dc.type Conference Paper en_US
dc.description.version Author's Original en_US
dash.depositing.author Kung, H.T. T.
dc.date.available 2012-12-06T18:31:48Z

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  • FAS Scholarly Articles [7106]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University

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