Radar image target detection system for typical active interference

Abstract

The invention discloses a radar image target detection system for typical active interference. The radar image target detection system comprises an active interference image data enhancement module, a data loader module, a network structure module, a network training module and a target positioning prediction module. The invention has the advantages of high reliability, high efficiency and suitability for seeker imaging target identification during active interference.

Description

technical field [0001] The invention belongs to the technical field of image processing and target recognition, in particular to a radar image target detection system facing typical active interference. Background technique [0002] Different from traditional optical images, the amount of information in radar images is seriously insufficient, and there are significant differences in imaging mechanism, target characteristics, and resolution. The imaging characteristics of radar echo data on the Doppler dimension are significantly different from those of optical images: the image contains a large amount of mixed active and passive noise such as clutter signals, and the pixel ratio of targets and interferers is extremely low compared to the entire image And the distribution is sparse. Traditional radar image target detection generally uses prior knowledge to extract features through candidate regions. The classic constant false alarm detection only statistically models the ba...

AI Technical Summary

Problems solved by technology

The classic constant false alarm detection only statistically models the background information, does not consider the complete modeling of the target information, only uses some features of the target imaging area to detect, does not make full use of the global features, and has a high false alarm rate; traditional feature extraction The method needs to consider information modeling or rule matching in a specific environment. However, in practical applications, the electromagnetic environment in which radar is located is harsh, and specific statistical modeling methods and rule matching methods are only applicable to a given environment.

At the same time, changes in the target's outline, orientation, size, and background interference will have a significant impact on the actual target detection. Manually set background information modeling and rule matching are difficult to achieve universality and have relatively large limitations.

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