Time-space correlation-based Video SAR moving target detection method

Abstract

The invention discloses a method for detecting a moving target of a Video SAR (Synthetic Aperture Radar) by utilizing space-time correlation. The method comprises the following specific steps of: step1, carrying out shadow detection on a single frame image of the Video SAR by adopting a basic static shadow detection model; step 2, obtaining a target motion parameter by adopting a matching searchmode, and obtaining a motion target estimation speed; step 3, carrying out track tracking on the moving target through a Kalman filtering tracking algorithm, and preliminarily screening a real movingtarget by using a track association method; and step 4, tracking the target in the step 3 by adopting a space-time correlation method, comparing the distance between the centroid of the shadow area ofthe first frame of image and the shadow area of the last frame of image and a given threshold after a period of time, and screening a real moving target shadow. Static shadows are removed from a high-probability moving target set, the accuracy and registration error robustness of Video SAR moving target detection are improved, and real moving targets can be screened out under the conditions thatthe moving target speed is high and the signal-to-noise ratio caused by target defocusing is low.

Description

Technical field [0001] The invention belongs to the field of radar technology, and particularly relates to a method for detecting moving targets, which can be used for detecting weak moving targets such as small unmanned aerial vehicles under the background of ground objects and blurry moving targets with unclear shooting. Background technique [0002] Moving target detection is to use statistical methods to obtain the background model, and update the background model in real time to adapt to changes in light and the scene itself, eliminate the influence of noise and background disturbance, and detect shadows in the HSV chromaticity space. Accurate sports goals. [0003] In the prior art, in view of the low signal-to-noise ratio SNR caused by the fast moving target speed during the downward viewing of the video synthetic aperture radar VideoSAR and the poor inter-frame spatiotemporal registration accuracy, the performance of the background elimination of ground objects is reduced, ...

AI Technical Summary

Problems solved by technology

This method can more accurately detect target shadows in SAR images, eliminate some false shadows that are too large or too small or do not conform to the target shape, and can complete preliminary target tracking, but this method only removes false shadows through simple target shapes shadows, and cannot completely remove stationary shadows

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