Kernel correlation filter for vehicle detection and recognition in SAR images

Zhuo Pan, Bin Hui Wang, Xin Gao, Yan Fei Wang

Research output: Contribution to journalArticlepeer-review


SAR target detection and recognition is sensitive to target's azimuth. To solve the problem, based on correlation theory and kernel feature analysis, a kernel correlation filter which is strongly robust to target's azimuth distortion is proposed. The novel filter exploits eigenvectors to reduce the dependence of the training set and extends linear combination of eigenvectors nonlinearly to improve the classification. Moreover, to keep the computation tractable in high dimensional space, the kernel function is employed. Comparative tests using MSTAR database demonstrate the kernel correlation filter performs high detection probability with low false alarm probability and implements target detection and recognition accurately without templates and target poses estimation.
Original languageEnglish (US)
Pages (from-to)1148-1152
Number of pages5
JournalDianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology
Issue number5
StatePublished - May 1 2009
Externally publishedYes

Bibliographical note

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

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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