Residual convolutional neural network and PCA dimensionality reduction fused SAR automatic target recognition method

Abstract

The invention discloses a residual convolutional neural network and PCA dimensionality reduction fused SAR automatic target recognition method. The method includes: acquiring an SAR target image dataand labeling a target category of the SAR target image data to form a training set; performing enhancement and expansion and pre-processing on training set image data, and constructing a residual convolutional neural network; inputting training samples into the network to perform training; inputting the training samples into the trained network model, and using feature vectors obtained after the samples pass all the hidden layers as a new training set; using the PCA dimensionality reduction method to perform dimensionality reduction on the obtained feature vectors, and then inputting the feature vectors into an SVM classifier to perform training; and finally pre-processing samples to be recognized, inputting the pre-processed samples to be recognized, obtaining feature vectors, performingPCA dimensionality reduction on the feature vectors, and using the trained SVM classifier to perform recognition. The method solves the problem that the existing SAR automatic target recognition technology has low recognition accuracy.

Description

technical field [0001] The invention belongs to the technical field of radar data processing, in particular to a SAR automatic target recognition method, which mainly solves the problem of low recognition accuracy in the prior art. Background technique [0002] Synthetic Aperture Radar (SAR) is an active high-resolution imaging radar, which can obtain images similar to visible light images under the weather conditions of cloud cover and low visibility. SAR has strong penetrating power, high resolution, and large-scale monitoring capabilities. These advantages make it have significant advantages in applications such as environmental monitoring, ocean monitoring, map mapping, and military reconnaissance. Therefore, the research on SAR radar-related technologies has attracted more and more attention from all over the world, and SAR image automatic target recognition is one of the most important technologies. [0003] Xidian University proposed a CNN-based SAR target recognitio...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the deficiencies of current SAR automatic target recognition technology, the purpose of the present invention is to provide a kind of SAR automatic target

Images