SAR image target recognition method based on kernel fuzzy Foley-Sammon transformation

A target recognition and image technology, applied in character and pattern recognition, instruments, computer components, etc., can solve problems such as inability to deal with linear inseparability, and achieve the effect of avoiding the disaster of dimensionality and high recognition accuracy

Inactive Publication Date: 2015-01-07
JIANGSU UNIV
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Problems solved by technology

However, since the fuzzy Foley-Sammon transformation method is still a linear feature extraction method, it cannot handle linear non-separable problems

Method used

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  • SAR image target recognition method based on kernel fuzzy Foley-Sammon transformation
  • SAR image target recognition method based on kernel fuzzy Foley-Sammon transformation
  • SAR image target recognition method based on kernel fuzzy Foley-Sammon transformation

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Embodiment

[0040] The sample data is the MSTAR (the Moving and Stationary Target Acquisition and Recognition) data set of DARPA and Wright Laboratory in the United States, which comes from: https: / / www.sdms.afrl.af.mil / datasets / matar / . Such as figure 2 As shown, four types of targets in the MSTAR dataset (2S1: artillery launch vehicle; BRDM2: armed transport vehicle; SLICY: double cylindrical metal body; ZSU23: anti-aircraft gun vehicle) are selected as identification objects, and 100 samples are taken for each category, a total of 400 SAR image sample, a sample with a radar viewing angle of 15 degrees.

[0041] Step 1, each SAR image is pulled into a row vector by column;

[0042] Stretch the SAR image into a row vector by column, for example, stretch a 128x128 SAR image into a 1x16384 row vector. In this way, 400 row vectors can be obtained from 400 SAR images.

[0043] Step 2: Use principal component analysis to perform dimension reduction processing, as follows:

[0044] The...

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Abstract

The invention discloses an SAR image target recognition method based on kernel fuzzy Foley-Sammon transformation. The method includes the steps that first, an SAR image is stretched according to columns to form row vectors and then dimension reduction processing is performed through principal component analysis; second, a fuzzy K-nearest neighbor algorithm and a fuzzy C-means clustering algorithm are used for achieving fuzzing of data, then, the characteristic vector corresponding to the maximum characteristic value of kernel fuzzy linear discriminant analysis is calculated and serves as the first characteristic vector in an optimal identified vector set of the method, next, the optimal identified vector set of the method is calculated according to the mutual orthogonal rule of neighbor identified vectors, and finally nonlinear transformation of fuzzy Foley-Sammon transformation is achieved through a kernel function. The problem that the linear impartibility problem of the fuzzy Foley-Sammon transformation is difficult to solve is solved, the nonlinear identification information of an SAR image radar target can be extracted, and the radar target identification accuracy rate is high.

Description

technical field [0001] The invention relates to the technical fields of pattern recognition and artificial intelligence, in particular to a SAR image target recognition method based on kernel fuzzy Foley-Sammon transformation. Background technique [0002] Synthetic Aperture Radar The spaceborne SAR system (SAR) of various countries is an all-weather, multi-view, airborne radar or spaceborne radar that can produce high-resolution images. SAR is widely used in military, agriculture, forestry, marine, geological and other fields. It is of great significance to promote the progress of national military science and technology, economic development and social security. SAR image system can realize target detection, location and classification functions. SAR image target recognition is an important part of SAR image analysis, mainly including two steps of SAR image feature extraction and classification. The feature extraction methods currently applied to SAR images include prin...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/213
Inventor 武小红杜辉武斌孙俊傅海军
Owner JIANGSU UNIV
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