Abstract
Automatic ground vehicle detection based on SAR imagery is one of the important military applications of SAR. A region-based generalized likelihood ratio test (GLRT) method is proposed in this paper, and this method combines the GLRT detection theory and image segmentation technology. First, the SAR imagery is roughly segmented as land clutter region and potential target region through the split and merge procedure often used for processing the original images. Then, based on the segmentation results, the reasonable statistical models for the data in the two regions are built respectively. Finally, with the knowledge of statistical characteristics of clutter and target, GLRT detection method is applied to the each pixel in the potential target region to obtain more accurate detection results. Experimental results based on real SAR data show that the proposed method can effectively detect the ground vehicle targets from the land clutter with excellent accuracy and speed.
Highlights
Synthetic Aperture Radar (SAR) is a kind of active imaging sensors, with its all-weather, all-time capabilities, etc, has been widely used in civil and military areas[1]
The region-based generalized likelihood ratio test (GLRT) method is applied to practical target detection in SAR image .And the proposed method is compared with VI-Constant False Alarm Rate (CFAR) detection method based on K distribution and Lognormal distribution
(c) Detection result by VI-CFAR method based on K distributionPfa0.00017˅
Summary
Synthetic Aperture Radar (SAR) is a kind of active imaging sensors, with its all-weather, all-time capabilities, etc, has been widely used in civil and military areas[1]. The Constant False Alarm Rate (CFAR) method derived from Bayesian decision theory is one of the most widely used detection methods in SAR image target detection areas. A GLRT region-based target detection method is proposed for the problem of military vehicle detection in complex scenes. The method combines image segmentation technique and GLRT target detection algorithm. On the basis of the already known background and target statistical properties, a more accurate GLRT detection algorithm is used to further determine the target in potential target area. The results show that the proposed method can detect military MATEC Web of Conferences targets from terrestrial scenes effectively, accurately and quickly
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