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Radar target recognition method based on sparse feature

A radar target and sparse feature technology, applied in radio wave measurement systems, instruments, etc., can solve the problems of complex radar target recognition systems and limited recognition accuracy.

Active Publication Date: 2013-07-31
北京深蓝空间遥感技术有限公司
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Problems solved by technology

[0004] Aiming at the above-mentioned problems existing in the prior art, in order to solve the problem that the radar target recognition system in the prior art is relatively complicated and the recognition accuracy is limited, the present invention provides a radar target recognition method based on sparse features, the radar target recognition method It avoids the dependence of recognition accuracy on target azimuth estimation, reduces the complexity of radar target recognition, and improves the processing efficiency and recognition accuracy of radar target recognition

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  • Radar target recognition method based on sparse feature

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Embodiment

[0115]In this embodiment, the data images published by the MSTAR public database are used to compare and evaluate the recognition effect of the radar target recognition method based on the sparse features of the present invention and other radar target recognition technologies. In this embodiment, ten types of radar targets publicly released by the MSTAR public database are selected as the data of the experimental database. These ten types of radar targets are all ground military vehicles or civilian vehicles, and have similar external shapes. Their radar target codes are BMP2 (infantry tank), BRDM2 (amphibious armored reconnaissance vehicle), BTR60 (armored transport vehicle), BTR70 (armored personnel carrier), D7 (agricultural bulldozer), T62 (T-62 main station tank), T72 (T-72 main station tank), ZIL131 (military truck), ZSU234 (self-propelled artillery tank) and 2S1 (self-propelled howitzer combat vehicle). The visible light images of the ten types of radar targets are as...

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Abstract

The invention provides a radar target recognition method based on a sparse feature. The method is used for improving the pertinence of data recognized by a radar target and reducing the computation burden of data processing by taking the sparse feature of a radar target image as a radar target image training sample and the recognition feature of a radar target to be measured; then, a sparse linear equation of the radar target to be measured is established according to the sparse feature of the training sample; then, the sparse linear equation is solved by using a Bayes compressed sensing algorithm, and the radar target to be measured is recognized by means of a compressed sensing theory instead of target azimuth estimation, so that the recognition complexity is lowered, and the recognition accuracy is prevented from depending on the target azimuth estimation; and meanwhile, the radar target recognition based on the compressed sensing theory also has favorable recognition performance under a noise environment, thus the problems that a radar target recognition system in the prior art is more complex and limited in recognition accuracy are solved, and the aims of increasing the processing efficiency for radar target recognition and improving the recognition accuracy are achieved.

Description

technical field [0001] The invention relates to the technical field of radar target recognition, in particular to a radar target recognition method based on sparse features. 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. The Synthetic Aperture Radar Auto Targets Recognition (SAR-ATR) system has important application value in the field of military defense. The goal of these radar automatic target identification systems is to detect and identify military targets over geographic areas using radar target images and various signal processing techniques. [0003] The recognition performance of the radar target automatic recognition system is mainly determined by the feature extraction and recognition algorithm. In order to obtain faster recognition processing efficiency and higher recognition accuracy, and...

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Application Information

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IPC IPC(8): G01S7/41
Inventor 张新征吴奇政秦建红谭熠峰
Owner 北京深蓝空间遥感技术有限公司
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