在自然空中非可控环境下, 飞机目标自动识别的难题之一是姿态变化和遮挡问题, 为此, 提出了一种基于稀疏表示的飞机目标识别方法, 该方法利用其稀疏表示系数进行飞机目标识别。与现有的方法相比, 该方法将飞机图像识别问题转化为求解待识别飞机图像序列关于训练飞机图像序列的稀疏表示问题, 是直接对原始飞机图像进行操作, 而不需要进行特征提取和选择过程, 由此提高了飞机识别算法的效率, 而且对飞机目标的姿态和遮挡变化具有较好的鲁棒性。在5种飞机图像数据集上的实验结果显示, 该方法对空中飞机类型识别是可行的, 其识别率高达90%以上。该方法为非线性、复杂的空中飞机目标识别提供了一种途径。

Under the natural non-controlled natural environment, one of the difficult problems in the automatic target recognition of aircraft is the attitude variation and occlusion. Therefore, we proposed an aircraft recognition method based on sparse representation. Compared with the existing methods, the highlight of the proposed method is to transform the target image recognition problem into a sparse representation problem of the training samples, which can process the original target images directly, and the processes of feature extraction and selection are not needed. Thus it possesses good robustness to the attitude and occlusion variations of the aircraft targets. Experimental results on 5 kinds of aircraft image data sets show that: the proposed method is feasible, and the recognition rate is above 90%. This method supplies a way for the identification of nonlinear and complex natural air images.