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中文摘要：
鉴于软着陆小天体过程中自主光学导航的状态估计问题,提出了一种针对小天体表面阴影区的提取与鲁棒匹配算法。首先,提取出阴影区中相对稳定的区域;然后,对提取出的阴影区域进行仿射归一化;最后,对仿射归一化后的阴影区域用多角度尺度不变特征变换（Multiple Angles Sift,MA-SIFT）描述子进行特征提取,并进行匹配与错匹配去除。在试验中,本文算法与SIFT算法进行了对比,结果表明,当图像间出现较大的视角变化时,利用本文算法能得到较高的正确匹配率。
英文摘要：
In this paper, a robust match algorithm for shadow area extraction in the process of visual autonomous navigation for attitudes estimation in planetary landing is proposed. First, the stable shadow areas areextracted. Then, an affine normalization algorithm is applied to normalize the shadow areas. At last, the featuresare extracted by using multiple angles sift（MA-SIFT） description operator, the matching pairs are got and the mismatches are removed. Comparative trial are conductedto compare with SIFT algorithm. It is shown that the matching rate can be maintained at a higher level by the use of the proposed algorithm, even there are large visual angle change between image pairs.
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