Novel SAR target detection algorithm using free training

Lina Zeng, Deyun Zhou, Xiaoyang Li, Kun Zhang

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

A detection method for Synthetic Aperture Radar (SAR) targets based on single sample feature extraction is proposed. Similar targets in a SAR image are detected according to the effective features of the selected single target sample. First, the potential targets of interest in a SAR image are detected, and the area features and texture features are extracted from the target sample and potential targets, respectively. Then, the false targets are eliminated from the potential targets via different matching methods. The proposed method for texture description in this paper can be adopted for targets with different attitudes by extracting the rotationinvariance features of the local region; these features can deal with speckle noise and deformation. The experimental results show the feasibility and validity of the proposed method.

Original languageEnglish
Pages (from-to)177-185
Number of pages9
JournalJournal of Radars
Volume6
Issue number2
DOIs
StatePublished - 28 Apr 2017

Keywords

  • Feature extraction
  • Object detection
  • Speeded up robust features
  • Synthetic Aperture Radar (SAR)

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