Radar target attribute scattering center feature extraction method based on sparse decomposition

Abstract

The invention discloses a radar target attribute scattering center feature extraction method based on sparse decomposition. The radar target attribute scattering center feature extraction method based on the sparse decomposition mainly solves the problems in an existing method capable of segmenting an image to extract attribute scattering center based on the radar image that models are unmatched, features are easy to lose, and parameter estimation accuracy is low. The implementation process includes the following steps: building a scattering center intensity threshold by using noise samples, conducting an intensive scattering center test in the radar image and confirming a values set of a scattering center parameter, obtaining a target attribute scattering center parameter super-resolution estimation set according to attribute scattering center models by using coordinate repeated decline technology to build a super-resolution dictionary through solving the problem of 0 norm optimization, and extracting geometric dimensioning features of the target and important components of the target according to the scattering center parameter set. The radar target attribute scattering center feature extraction method based on the sparse decomposition is capable of effectively extracting the target attribute scattering center and the super-resolution scattering center parameter, accurately estimating the geometric dimensioning features of the target and the important components of the target, and can be used for radar target classification and identification.

Description

technical field [0001] The invention belongs to the technical field of radar, and relates to a feature extraction method of a radar target attribute scattering center, which can be used for estimating the geometric dimensions of a target and its important components, and providing important feature information for target classification and recognition. Background technique [0002] Radar imaging technology was developed in the 1950s, and radar images are two-dimensional scattering maps of targets. Traditional radar imaging is based on the point-scattering model, which only contains the location information of target scattering points, but the identification features constructed only by using the location information of target scattering points cannot fully represent the essential properties of targets in radar images. In the optical region, the high-frequency electromagnetic scattering response of the extended target can be approximated by the sum of the electromagnetic scat...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to propose a method for feature extraction of scattering centers of radar target attributes based on sparse decomposition, so as to solve the problems of model mismatch, easy loss of features and low accuracy of parameter estimation in existing methods

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