SAR (Synthetic Aperture Radar) image target recognizing method based on nuclear scale tangent dimensionality reduction

Abstract

The invention discloses an SAR (Synthetic Aperture Radar) image target recognizing method based on nuclear scale tangent dimensionality reduction, which mainly solves the problem of low SAR image target recognizing rate of the traditional method. The method comprises the following steps of: preprocessing the selected image with the known class information and the image to be tested to acquire a training set and a testing set; mapping the training set to a higher dimensional space by the Gaussian kernel function, and respectively constructing an intra-class dissimilarity matrix and an extra-class dissimilarity matrix by using the mapped high dimensional feature as input, thereby acquiring a Laplacian matrix based on the nuclear scale tangent; carrying out feature decomposition on the matrix to acquire an optimal projection matrix; respectively projecting a training sample and a testing sample to a subspace formed by expansion of projection matrix vectors to acquire a new training set and a new testing set; and inputting the new training set and the new testing set into a support vector machine for classification and recognition to acquire the class information of the tested image. The method of the invention has the advantages of high recognition rate and good robustness and can be used for recognizing SAR images.

Description

technical field [0001] The invention belongs to the technical field of image processing, relates to a target recognition method, and can be applied to synthetic aperture radar SAR image target recognition and face recognition. Background technique [0002] The unique advantages of synthetic aperture radar (SAR) technology in the detection of ground targets, especially stationary targets, and its good application prospects in the fields of modern battlefield perception and ground strikes have made the automatic target recognition technology ART based on SAR images received a lot of attention. more and more attention. At present, many research institutions at home and abroad have carried out research on automatic target recognition technology for SAR images, many of which are based on moving and stationary target detection and recognition Moving and Stationary Target Acquisition and Recognition, MSTAR database, the database Provided by the U.S. Defense Advanced Research Proje...

AI Technical Summary

Problems solved by technology

[0006] However, both Kernel Fisher Discriminant Analysis and Fisher Linear Discriminant Analysis are based on the assumption that each type of sample is subject to a Gaussian distribution. This assumption limits the practical application of Kernel Fisher Discriminant Analysis and Fisher Linear Discriminant Analysis.

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