基于直方图统计量的逆合成孔径雷达目标识别

摘要

将原用于人脸识别的基于Gabor局部二进制模式的识别技术用于逆合成孔径雷达（ISAR）像的雷达目标识别，对算法进行了改进，取得了较好的识别效果。将ISAR像进行Gabor小波变换，提取不同尺度和方向的Gabor幅值图谱；然后把幅值图谱分成小的子区域，用多尺度局部二值模式提取空域增强的直方图作为特征，最后在X2统计量作为不相似度量计算的特征空间里，采用最近邻分类器完成五类目标的分类识别。与目前已有的几种典型IsAR目标识别方法进行了对比，结果表明：该方法是可行且有效的，能够明显地提高识别率。%Local Gabor binary patterns （LGBP） method in face recognition is im- proved and applied in inverse synthetic aperture radar （ISAR） target recognition. Firstly, the corresponding Gabor magnitude maps （GMMs） are obtained by convol- ving the enhanced ISAR image with multi-scale and multi-orientation Gabor filters. Then, each GMM is divided into small regions from which multi-scale block local binary pattern is used to extract histogram features. At last, five-type aircraft mod- els are classified by using a nearest neighbor classifier with Chi square as a dissimi- larity measure in the computed feature space. Compared with other recognition methods, the numerical results show that the proposed method is effective and has higher recognition performance.