针对SAR图像特征点匹配问题，提出了一种基于Facet模型的特征点检测方法。首先基于Facet模型对局部区域做灰度曲面最佳拟合，然后计算拟合曲面中心点的二阶方向导数，取二阶方向导数极大值小于零的点作为潜在特征点，最后通过对极大值的绝对值归一化和局部非极大值抑制提取特征点。实验结果表明，该算法可有效检测特征点，算法的实时性优于传统的SIFT算法。

For the feature point matching of SAR images used in navigation system, a feature point extraction approach is proposed based on Facet model.Firstly, the image intensity surface is well fitted through the Facet model.Then the second-order directional derivative of the center point of the fitting surface is calculated out, and the point whose second-order directional derivative is less than zero is taken as the potential feature point.Through normalization of absolute values for maximum values of the potential feature points and local non-maxima suppression, the feature points are obtained.Experimental results show that the proposed algorithm can successfully detect the feature point, and the real-time performance of the algorithm is better than that of the traditional SIFT algorithm.