ISAR ship target image domain enhanced recognition method based on loop generative adversarial network

Abstract

The invention discloses an ISAR ship target image domain enhanced recognition method based on a loop generative adversarial network, and relates to the field of radar target recognition. The objectiveof the invention is to solve the problem of low accuracy of ship type identification in the prior art. The method comprises the steps: preprocessing ship original ISAR images and original optical images of various ship types stored in a database to obtain an original ISAR image data set and an original optical image data set; taking the original ISAR image data set and the original optical imagedata set as a training set, and training the training set by adopting a loop generative adversarial network to obtain a trained loop generative adversarial network; preprocessing a to-be-tested ship ISAR image or optical image to obtain a to-be-tested ISAR image or optical image; analyzing the to-be-tested ISAR image or optical image by adopting the trained loop generative adversarial network to obtain a new image with optical characteristics and ISAM characteristics at the same time; and analyzing the new image by adopting a convolutional neural network to obtain a ship type. The method is used to identify images.

Description

technical field [0001] The invention relates to a ship ISAR image recognition method. It belongs to the field of radar target recognition. Background technique [0002] Inverse synthetic aperture radar (ISAR) completes target imaging by transmitting signals to detection targets and receiving target echoes. Existing classification recognition method has: 1, adopt the application of invariant matrix feature and morphological feature on the two-dimensional ISAR image recognition of flying target, adopt nearest neighbor classifier and neural network to classify, have obtained good effect; [0003] 2. Using the improved MUSIC-2D method to reconstruct the radar target image, using the Fourier descriptor and moment invariant features, and using the self-organizing neural network to realize the classification of different military aircraft; [0004] 3. A SVM classifier system based on various morphological features is proposed, and a good classification effect is achieved on the m...

AI Technical Summary

Problems solved by technology

[0014] The present invention is to solve the existing problem of low accuracy of class identification of ships

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