A Space Target Recognition Method Based on Compressive Sensing

Small sample space target recognition is a difficult problem in applications because the limited training samples cannot lead to satisfactory recognition accuracy. Combined with novel compression perception theory, we propose a new space target recognition method based on compressive sensing. This method avoids the sophisticated image preprocessing and feature extraction process. Firstly, a sparse representation dictionary is constructed according to the training samples. Secondly, the linear measurements of test samples are obtained by measurement matrix. Finally, the classification and recognition are done through solving an optimization problem. Simulation experiment results show that the proposed method has good recognition performance and stability.