多方位角图像决策融合的SAR目标识别

多方位角图像决策融合的SAR目标识别 SAR target recognition using multiple views decision fusion 宦若虹 1 first-author 杨汝良 2 浙江工业大学计算机科学与技术学院 浙江工业大学计算机科学与技术学院 中国科学院电子学研究所 中国科学院电子学研究所 提出了一种基于多方位角图像决策融合的合成孔径雷达（SAR）图像目标识别方法。对目标切片图像用二维小波分解和主成分分析提取特征向量,利用支持向量机对特征向量进行分类,用贝叶斯方法对目标多幅不同方位角下图像的分类输出进行决策融合,得到最终类别决策。用MSTAR数据库中3个目标进行识别实验,实验结果表明,对3幅以上不同方位角的图像进行决策融合时,该方法可显著提高目标的正确识别率。该方法是一种有效的SAR图像目标识别方法。 In this paper, new synthetic aperture radar （SAR） image target recognition approach based on multiple views decision fusion is presented. Image chips are represented as feature vectors by 2-D wavelet transformation and principal component analysis algorithm. The feature vectors are classified by using algorithms of support vector machine （SVM）. After multiple views of the same vehicle collected at different aspects classified by SVM, the outputs are then fused using Bayesian approach and the final classification decision is generated. Experiments are implemented with three class targets in Moving and Stationary Target Acquisition and Recognition （MSTAR） Program database. Experimental results indicate that there are significant target recognition performance benefits in the probability of correct classification when three or more views are used for decision fusion. Therefore, the approach proposed is an effective method for SAR image target recognition. 合成孔径雷达（SAR） 目标识别 多方位角图像 决策融合 贝叶斯 synthetic aperture radar （SAR） target recognition multiple views decision fusion Bayesian TN957.52 浙江省科技厅面上工业项目（编号:2009C31002）~~ 2021-06-09 2 14