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

Abstract

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 the time dimension and the space dimension of the SAR sequence image, and the accuracy of SAR target classification and recognition is improved. The method can be used for automatic target identification based on SAR sequence images.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a synthetic aperture radar SAR sequence image classification method, which can be used to realize automatic target recognition based on the SAR sequence image. Background technique [0002] Synthetic aperture radar (SAR) has the characteristics of all-weather, all-time, and high-resolution, and is widely used in military reconnaissance, battlefield perception, and geographic information collection. Automatic target recognition (ATR) is an algorithm based on a computer system that acquires data from sensors, extracts features, and automatically gives target category attributes. In recent years, the automatic target recognition (ATR) technology based on synthetic aperture radar (SAR) sequence images has been continuously developed, and has received extensive attention in the research of radar target recognition. [0003] At present, the main idea of ​​the target cla...

AI Technical Summary

Problems solved by technology

This method effectively extracts the spatial features of SAR images, but the problem still exists in this method is that it does not effectively use the time information between image sequences, so the recognition accuracy rate is low

Although this method has good robustness to the change of viewing angle, the image sequence information is incoherent when constructing the sample set, and the change characteristics between image sequences are lost, so the recognition performance of the changing target still needs to be improved.

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