Clustering Algorithm Improvement in SAR Target Detection

The synthetic aperture radar (SAR) auto target recognition (ATR) system developed at Lincoln Laboratory is a standard system for target detection/recognition. It has three main stages: a prescreener, a discriminator and a classifier. The clustering algorithm between the prescreener stage and the discriminator stage is used to cluster the multiple detections of a single target to form a region of interest (ROI). This paper introduces the steps of the common clustering algorithm and analyzes its disadvantages. We improve the common clustering algorithm from two aspects of the read sequence of image data and the calculation means of clustering quasi-center coordinates. The clustering results based on two actual images testify efficiency of clustering algorithm improvement.