SAR object identification method based on range profile time-frequency diagram non-negative sparse coding

Abstract

The invention provides an SAR object identification method based on range profile time-frequency diagram non-negative sparse coding. The method utilizes non-negative sparse coding, and in the whole identification process, SAR image objects do not need azimuth angle estimation, thereby reducing the identification complex degree, avoiding the dependence of identification accuracy on object azimuth angle estimation, and helping to improve the object identification rate; and meanwhile, radar object identification is carried out based on the range profile time-frequency diagram non-negative sparse coding technique, and good identification performance is also achieved in the noise environment, thereby not influencing identification effect when not-high image quality, due to factors of defocusing or signal to noise ratio and the like during the object moving, is caused, and helping to improve the robustness performance of the radar object identification.

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 non-negative sparse coding of range image time-frequency graphs. 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. Due to the active imaging characteristics of SAR and the complex scattering mechanism in the imaging process, the target characteristics in SAR images are very different from optical images, which brings many difficulties to target feature extraction and recognition. [0003] Researchers have studied many target recognition algorithms based on two-dimensional SAR images. Among them, the most direct method is to directly use SAR images as features for target recognition. Another radar target recognition method is based on wavelet transform...

AI Technical Summary

Problems solved by technology

[0005] In view of the above-mentioned problems existing in the prior art, in order to solve the problem that the SAR image target recognition in the prior art needs to estimate the target azimuth angle and the recognition accuracy is limited, the present invention provides a non-negative sparse coding based on the time-frequency map of the range image The SAR target recognition method, the radar target recognition method uses non-negative sparse representation to model and feature extraction of non-negative time-frequency plane data, does not need to estimate the target azimuth angle of the SAR image, and can avoid defocus or signal noise Ratio and other factors affect the target recognition effect, improve the accuracy of SAR target recognition

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