Abstract：SAR image of the ground target contains the target region formed by the scattered echoes of the target as well as the shadow area. However, the characteristics of the two areas are essentially different, therefore the traditional SAR image Automatic Target Recognition (ATR) methods use mainly target area information alone or shadow region only for recognition. This paper presents a joint sparse representation model by combining images of the shadow region and target region. By using the ζ1\ζ2 norm minimization method to solve the joint sparse representation model, the SAR image target recognition is achieved by minimizing the joint reconstruction error. Recognition results on Moving and Stationary Target Acquisition and Recognition (MSTAR) data sets show that the joint sparse representation model can effectively fuse the information within the target region and shadow region, and it has much better recognition performance than the methods using only the target or shadow area information of the image.
丁军, 刘宏伟, 王英华, 王正珏, 齐会娇, 时荔蕙. 一种联合阴影和目标区域图像的SAR目标识别方法[J]. 电子与信息学报, 2015, 37(3): 594-600.
Ding Jun, Liu Hong-Wei, Wang Ying-Hua, Wang Zheng-Jue, Qi Hui-Jiao, Shi Li-Hui. SAR Target Recognition by Combining Images of the Shadow Region and Target Region. , 2015, 37(3): 594-600.
2015, Vol. 37 
