<title>ATR subsystem performance measures using manual segmentation of SAR target chips</title>

Abstract

Target recognition research for Synthetic Aperture Radar (SAR) has been made easier with the introduction of target chip sets. The target chips typically are of good quality and consist of three regions: target, shadow and background clutter. Target chip sets allow recognition researchers to bypass the quality filtering and detection phases of the automatic recognition process. So, the researcher can focus on segmentation and matching techniques. A manual segmentation process using supervised quality control is introduced in this paper. Using 'goodness of fit' measures the quality of manual segmentation on SAR target chips is presented. Using the expected metrics associated with the manual segmentation process, the performance of automated segmentation techniques can be evaluated. The approach of using manual segmentation to evaluate the performance of automated segmentation techniques is presented by demonstrating the results on a simple automated segmentation technique that incorporates speckle removal and segmentation.