SAR (Synthetic Aperture Radar) image target identification method based on multilinear principal component analysis and tensor analysis

Abstract

The invention discloses an SAR (Synthetic Aperture Radar) image target identification method based on multilinear principal component analysis and tensor analysis. The method comprises the following steps that: constructing a four-order tensor training sample; utilizing the multilinear principal component analysis to obtain a multilinear projection matrix; constructing a core tensor; carrying out linear discriminant analysis on the core tensor to obtain the weight vectors of one group of linear discrimination functions; and carrying out classified identification on test samples. By use of the method, the four-order tensor sample is constructed for the SAR image, the multilinear principal component analysis is adopted to extract features, image structure information is effectively kept, and a correct recognition rate of a target is improved.

Description

technical field [0001] The invention relates to the fields of image processing, feature extraction, target recognition and the like, and in particular to the field of synthetic aperture radar image target recognition. Background technique [0002] The general process of synthetic aperture radar (Synthetic Aperture Radar, SAR) image target recognition is: image preprocessing, feature extraction and classification recognition. The premise and key of classification recognition lies in feature extraction. In order to achieve a certain recognition accuracy and speed, it is necessary to select the feature quantity that best characterizes the characteristics of the original SAR image data and has the most distinguishing features as the basis for recognition. High-precision classification and recognition of images using features requires that the selected features have good intra-class similarity and inter-class difference. The feature extraction methods of SAR images mainly inclu...

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Problems solved by technology

[0004] In order to overcome the problem of loss of image structure information and low recognition rate caused by principal component analysis feature extraction in current synthetic aperture radar image target recognition, the present invention proposes a synthetic aperture radar image target recognition based on multi-linear principal component analysis and tensor analysis method, this method constructs fourth-order tensor samples for synthetic aperture radar images, and uses multi-linear principal component analysis to extract features, effectively retains image structure information, and improves the correct target recognition rate

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