SAR sequence image classification method based on space-time joint convolution

The invention discloses an SAR (Synthetic Aperture Radar) sequence image classification method based on space-time joint convolution, which mainly solves the problems of insufficient time informationutilization and low classification accuracy due to the fact that only single image features are utilized in the existing SAR target recognition technology. The method comprises the following steps: 1)generating a sample set, and generating a training sequence sample set and a test sequence sample set from the sample set; 2) constructing a space-time joint convolutional neural network; 3) traininga space-time joint convolutional neural network by using the training sequence sample set to obtain a trained space-time joint convolutional neural network; and 4) inputting the test sequence sampleset into the trained space-time joint convolutional neural network to obtain a classification result. According to the method, the space-time joint convolutional neural network is utilized to extractthe change characteristics of