Automatic space target recognition based on sequential images

According to the space target imaging characteristics in long/short range, an automatic target recognition method with multiple scales is proposed based on sequential images. By integrating varying scale, varying attitude and image features, multi-scale classifiers were constructed with support vector machines, and attitude identification was conducted through RBF neural networks. Then the estimation on the confidence of recognition results, the weight of varying attitude between two adjacent images, and the weight of target scale was discussed respectively. And the final recognition result was obtained by fusion judgment, according to the current recognition result and the previous recognition result. Tests on 10 classes of video data simulated by STK show that the proposed method is effective. For space targets in long range, owing to small pixels, the recognition accuracy is low with only current image, while the high recognition accuracy can be achieved using sequential images.