An Improved GLRT Method for Target Detection in SAR Imagery
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106 Jiangsu, China
a Corresponding author: email@example.com
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.
Key words: SAR Imagery / Target Detection / Image Segmentation / Statistical Model / GLRT
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