The mobility of the ground time-sensitive targets is very strong, and the target attitude information can not be accurately predicted, which may lead to identification difficulties.SIFT algorithm exhibits great performance under a variety of image transformations, such as rotation, scale, illumination and other distortions, but it can only work within a small range of perspective transformation.When encountering large perspective transformation, the recognition rate of SIFT becomes lower.To solve this problem, a ground time-sensitive target recognition method based on edge orientation features was proposed.Firstly, integral images and Haar wavelet template were utilized to calculate the image gradient field, taking the points with maximum module value as feature points.Two points that meet the distance constraints were combined to form a pair of feature points, enhancing the peculiarity of the feature point pairs by using mutual calibration method.The gradient orientation was taken as the matching basis to achieve target recognition.Experimental results show that the recognition method is feasible and effective, which can keep stable within a wide range of perspective transformation.In the experiment, targets within the perspective of 45° can be identified correctly.The method has strong robustness to the perspective transformation, and performs better than SIFT algorithm.