SAR Target Recognition Method Based on Azimuth Correlation Dynamic Dictionary Sparse Representation

Abstract

The present invention provides a SAR target recognition method based on the sparse representation of the azimuth-related dynamic dictionary. It first estimates the azimuth of the SAR image as the test sample, and then calculates a relevant azimuth range according to the azimuth estimation value, thereby based on each A sparse feature training sample set composed of a collection of sparse feature matrices of training samples, the sparse feature matrix of the training samples whose azimuth values ​​are outside the range of the relevant azimuth angle in the sparse feature training sample set is set to a zero matrix, and only the azimuth angle is retained The sparse feature matrix of the training sample whose value is within the range of the relevant azimuth angle constitutes the sparse feature azimuth angle-related dynamic dictionary corresponding to the test sample, and then performs sparse representation classification and recognition, which greatly reduces the calculation of sparse coding and sparse reconstruction. The recognition processing efficiency is improved, and the interference of the training samples with irrelevant azimuth angles on the target recognition of the test samples is also reduced, so that the recognition accuracy is also improved.

Description

technical field [0001] The invention relates to the technical field of radar target recognition, in particular to a SAR target recognition method based on sparse representation of an azimuth-related dynamic dictionary. Background technique [0002] Synthetic Aperture Radar (SAR) technology is a pulse radar technology that uses mobile radar mounted on satellites or aircraft to obtain radar target images in high-precision geographic areas. Synthetic aperture radar is an active microwave imaging system, which can provide high-resolution images of the target area by irradiating the target area with electromagnetic waves and analyzing the echo signals. It has all-weather, all-day working ability and certain penetration ability. In view of its advantages, it is widely used in fields such as mineral exploration, marine environment monitoring and military defense. In the field of military defense, the research on target recognition is the most extensive, so the research on SAR Aut...

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Problems solved by technology

[0005] In view of the above-mentioned problems in the prior art, the present invention provides a SAR target recognition method based on the sparse representation of the azimuth-related dynamic dictionary, which can improve the recognition processing efficiency and recognition accuracy of radar target recognition based on SAR images, for Solve the problems of complicated sparse coding and sparse reconstruction operation process, insufficient recognition processing efficiency and target recognition accuracy in the SAR target recognition method using sparse representation classification in the prior art

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