SAR image target detection method based on unsupervised domain adaptive CNN

Abstract

The invention discloses an SAR image target detection method based on an unsupervised domain adaptive CNN, and provides the SAR image target detection method based on the unsupervised domain adaptiveCNN for SAR image target detection mainly aiming at the defects in the prior art. The method comprises the following steps: (1) generating a source domain data set; (2) generating a target domain training set and a target domain test set; (3) constructing a multi-layer feature domain adaptive network; (4) training a cyclic consistency generative adversarial network; (5) training a multi-layer feature domain adaptive network; (6) training the Faster R-CNN by using an iterative pseudo-marking method; and (7) performing position detection on the test SAR image in the target domain test set. By means of knowledge of marked source domain data, the method has the advantages that the accuracy is high, and marked SAR images do not need to be used for training target detection in a target domain.

Description

technical field [0001] The invention belongs to the technical field of radar image processing, and further relates to a synthetic aperture radar SAR (Synthetic Aperture Radar) image target based on an unsupervised domain adaptive convolutional neural network CNN (Convolutional Neural Network) in the technical field of radar image automatic target recognition Detection method. The present invention can be used to detect objects of interest from SAR images, such as ground vehicle detection. Background technique [0002] Synthetic aperture radar (SAR) has the advantage of providing remote sensing images under all-weather and all-weather conditions, and is widely used in military and civilian fields. With the rapid development of radar imaging technology, the field of SAR automatic target recognition is developing rapidly. SAR image target detection, as a challenging task in SAR automatic target recognition, has received extensive attention. Constant false alarm rate CFAR is ...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to address the deficiencies in the above-mentioned prior art, and propose a SAR image target detection method based on unsupervised domain adaptive CNN, which is used to solve the problem of low detection accuracy in the prior art and the need to use marked image training targets Detect network problems

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