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Volume 38 Issue 10
Oct.  2016
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Article Navigation >  Journal of Electronics & Information Technology  > 2016  >  38(10): 2461-2467
WU Jiani, CHEN Yongguang, DAI Dahai, CHEN Siwei, WANG Xuesong. Target Recognition for Polarimetric HRRP Based on Fast Density Search Clustering Method[J]. Journal of Electronics & Information Technology, 2016, 38(10): 2461-2467. doi: 10.11999/JEIT151457
Citation: WU Jiani, CHEN Yongguang, DAI Dahai, CHEN Siwei, WANG Xuesong. Target Recognition for Polarimetric HRRP Based on Fast Density Search Clustering Method[J]. Journal of Electronics & Information Technology, 2016, 38(10): 2461-2467. doi: 10.11999/JEIT151457
shu

Target Recognition for Polarimetric HRRP Based on Fast Density Search Clustering Method

doi: 10.11999/JEIT151457
  • 1.

    (State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, National University of Defense Technology, Changsha 410073, China)

  • 2.

    (Beijing Institute of Tracking and Telecommunications Technology, Beijing 100094, China)

Funds:

The National Natural Science Foundation of China (61302143, 61490693, 41301490), The National 863 Program of China (2013AA122202)

  • Received Date: 2015-12-24
  • Rev Recd Date: 2016-06-08
  • Publish Date: 2016-10-19
    Abstract
  • A classification algorithm based on the fast density search clustering method is proposed for polarimetric High Resolution Range Profile (HRRP) of man-made target. The polarization and frequency features are used to discriminate scattering centers in order to obtain the feature vectors for target classification. After that, the fast density search clustering method is applied to classifying the man-made target. The experiments show that the feature vectors for target classification can describe the structural properties of the target and can easily be classified. The fast density search clustering method operates simply and efficiently and can be applied to the man-made target classification with excellent performance.
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    • References(22)
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