Residual convolutional neural network and PCA dimensionality reduction fused SAR automatic target recognition method
A technology of convolutional neural network and automatic target recognition, which is applied in neural learning methods, biological neural network models, character and pattern recognition, etc., can solve the problems of low recognition accuracy and achieve high recognition rate, good recognition effect, and automation high degree of effect
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[0053] The present invention will be described in detail below according to the accompanying drawings.
[0054] refer to figure 1 , the specific implementation steps of the present invention are as follows:
[0055] 1) Obtain the SAR target image data and mark it according to the target category to form a training set.
[0056] For the multiple types of targets involved in the target recognition task, several SAR images are collected for each type as training samples.
[0057] 2) Perform data enhancement and preprocessing on the given training set images.
[0058] 2.1) Data enhancement:
[0059] Perform random translation, flip, rotation and scaling operations on each SAR image in the training set, and generate derived training samples with the same label as the original training samples;
[0060] 2.2) Preprocessing:
[0061] 2.2.1) Use the filtering algorithm to process the SAR image to suppress coherent speckle noise. The pixel value after image filtering is calculated ...
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