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Multi-view radar target recognition based on multitask compressive sensing

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  • Shengqi Liu
  • Ronghui Zhan
  • Qinglin Zhai
  • Wei Wang
  • Jun Zhang

Abstract

A novel multitask compressive sensing (MtCS)-based method for multi-view radar automatic target recognition is presented in the paper. The sparse representation vectors recovered jointly via MtCS are used as recognition features, and classification is performed according to minimum reconstruction error criterion. Compared to the conventional methods, the proposed method has a significant advantage of exploiting the statistical correlation among multiple views for target recognition. Experiments were conducted using a synthetic vehicle target data-set and the moving and stationary target acquisition and recognition database. The results show that the proposed method achieves promising recognition accuracy, and is robust with respect to noisy observations and complex target types.

Suggested Citation

  • Shengqi Liu & Ronghui Zhan & Qinglin Zhai & Wei Wang & Jun Zhang, 2015. "Multi-view radar target recognition based on multitask compressive sensing," Journal of Electromagnetic Waves and Applications, Taylor & Francis Journals, vol. 29(14), pages 1917-1934, September.
    • Handle: RePEc:taf:tewaxx:v:29:y:2015:i:14:p:1917-1934
    DOI: 10.1080/09205071.2015.1067647
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