电波科学学报2012，Vol.27Issue(5)：1024-1029,6.
滑窗加权泽尼克矩特征的雷达目标识别技术
Automatic target recognition of MSTAR SAR images based on sliding window weighted Zernike features
摘要
Abstract
SAR images aspect sensitivity and speckle noise have a significant influence on SAR image target recognition effect. On this basis, a novel automatic target recognition method based on moving and stationary targets acquisition and recognition synthetic aperture radar(MSTAR SAR) images is proposed. At first, the target and the shadow were obtained from speckle noise by using delaunay tringulation and Growcut algorithm. Then, Zernike moments were calculated via Zernike transform, and sliding window weighted Zernike(SWWZ) moments as the feature invariants were extracted. Finally, the recognition results were obtained through utilizing the nearest neighbor criterion. The simulation results show that SWWZ moments as the feature invariants overcome the SAR aspect sensitivity and improve the recognition rate effectively, and also the proposed approach to MSTAR SAR images recognition is effective and robust.关键词
合成孔径雷达图像/图像分割/泽尼克矩/滑窗加权/自动目标识别Key words
synthetic aperture radar images/image segmentation/Zernike moment/sliding window weighted/automatic target recognition分类
信息技术与安全科学引用本文复制引用
崔艳鹏,胡建伟,李英,艾小凡..滑窗加权泽尼克矩特征的雷达目标识别技术[J].电波科学学报,2012,27(5):1024-1029,6.基金项目
基金项目：中央高校基本科研业务费专项资金资助 （）
