Label consistent K-SVD for sparse micro-doppler classification

Tools

Coutts, Fraser K. and Gaglione, Domenico and Clemente, Carmine and Li, Gang and Proudler, Ian K. and Soraghan, John J.; (2015) Label consistent K-SVD for sparse micro-doppler classification. In: 2015 IEEE International Conference on Digital Signal Processing (DSP). IEEE, GBR, pp. 90-94. ISBN 978-1-4799-8058-1 (https://doi.org/10.1109/ICDSP.2015.7251836)

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Abstract

Secondary motions of targets observed by radar introduce non-stationary returns containing the so-called micro-Doppler information. This is characterizing information that can be exploited to enhance automatic target recognition systems. In this paper, the challenge of classifying the micro-Doppler return of helicopters is addressed. A robust dictionary learning algorithm, Label Consistent K-SVD (LC-KSVD), is applied to identify effectively and efficiently helicopters. The effectiveness of the proposed algorithm is demonstrated on both synthetic and real radar data.

ORCID iDs

Coutts, Fraser K. ORCID logoORCID: https://orcid.org/0000-0003-2299-2648, Gaglione, Domenico ORCID logoORCID: https://orcid.org/0000-0001-7401-1659, Clemente, Carmine ORCID logoORCID: https://orcid.org/0000-0002-6665-693X, Li, Gang, Proudler, Ian K. and Soraghan, John J. ORCID logoORCID: https://orcid.org/0000-0003-4418-7391;
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