Automatic vehicle target recognition in full SAR image scenes

Zhuo Pan, Xin Gao, Yan Fei Wang, Bin Hui Wang, Jian Hong Xie

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


A new method is presented for automatic target recognition in full synthetic aperture radar (SAR) image scenes. As SAR target classification is sensitive to target's azimuth, based on correlation filter theory and kernel feature analysis, a nonlinear correlation filter is provided, it can tolerate a distortion of target's azimuth. The novel filter exploits eigenvectors to reduce the dependence of the training set and extends the linear combination of eigenvectors nonlinearly to improve the classification performance. Moreover, to keep the computation tractable in high dimensional space, the kernel function is employed. The tests using MSTAR database demonstrate the scheme is practical and the novel filter implements target classification efficiently and accurately without templates and target poses estimation.
Original languageEnglish (US)
JournalXi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
Issue number7
StatePublished - Jul 1 2009
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-09-21

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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