SAR target identification method based on scattering point and K-center one-class classifier

Abstract

The invention discloses an SAR target identification method based on a scattering point and a K-center one-class classifier, and mainly overcomes the defects that in the prior art the difference of a target from a clutter false-alarm is not revealed in the view of the nature of radar imaging, and the total identification accuracy rate is low. According to the technical scheme, the SAR target identification method comprises the following steps: 1) detecting the clutter false-alarm of an SAR image, and extracting sections; 2) selecting sections with real targets from the extracted sections, thereby forming a training sample; 3) extracting a scattering point matrix from the training sample according to a scattering point model, and performing amplitude 2-norm normalization; 4) performing K-center clustering on the scattering point matrix of the training sample, thereby obtaining a cluster center; 5) calculating an identification threshold Thr of the K-center one-class classifier; 6) calculating the minimum bidirectional Hausdorff distance of a testing sample and the cluster center; 7) judging whether the testing sample is a target or not according to the distance. Through the adoption of the SAR target identification method, the false-alarm rate of clutter false-alarm is reduced, the total identification accuracy rate is effectively increased, and the SAR target identification method is applicable to artificial targets such as vehicles with remarkable strong scattering point distribution characteristics in SAR images.

Description

technical field [0001] The invention belongs to the technical field of radar and relates to a target detection and identification method, which can be used for identification of man-made targets with significant distribution characteristics of strong scattering points, such as vehicles, in SAR images. Background technique [0002] Radar imaging technology was developed in the 1950s, and developed by leaps and bounds in the next 60 years. At present, it has been widely used in military, agriculture, forestry, geology, ocean, disaster, surveying and mapping and many other fields. Synthetic aperture radar (SAR) has the characteristics of all-weather, all-time, high resolution and strong penetrating power, and has become an important means of earth observation and military reconnaissance. [0003] SAR image interpretation is the frontier topic of current SAR application, and it is also a hot field of earth observation technology application in recent years, which has important r...

AI Technical Summary

Problems solved by technology

These characteristics are useful for the separation of targets and clutter false alarms, but these features do not reveal the difference between targets and clutter false alarms from the essence of radar coherent imaging, and the total accuracy of identification is low

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