<title>Probability distributions of polarimetric target and clutter data for search and rescue</title>

Abstract

ABSTRACT In this paper we empirically examine the probability of detection (PD) and false alarm rate (FAR) for crash site detectionusing polarimetry to discriminate between aircraft target signatures within natural clutter. To date, the search and rescueprogram has tried several automatic target recognition (ATR) algorithms from the literature. While PD seems reasonablewith these algorithms, the FAR is too high (—iO's per square kilometer). The objective of our analysis is to determine if thisis a limitation of the ATR algorithms tried, or if this is the best that can be hoped for given the polarimetric statistics of thetarget and clutter.Keywords: Search and Rescue, Polarimetry, Cameron Transformation, Synthetic Aperture Radar 1. INTRODUCTION Beaconless search and rescue utilizes a synthetic aperture radar (SAR) system to search for downed aircraft in remoteregions. Low frequency SAR is capable of quickly imaging large areas and penetrating bad weather and foliage cover.Coupled to a computer processing system, that includes automatic crash site detection algorithms, SAR has the potential tobecome a significantly useful search tool. We are currently determining the fundamental limits on the probability ofdetection versus the false alarm rate for crash site detection using radar polarimetry. In this paper we present our analysis ofdata from Half Moon Bay (HMB), California, Teton National Park, Wyoming, and from scale-model tests done by SystemPlanning Corporation (SPC), Virginia.