Validation of an automatic vessel detection algorithm using SAR data and known vessel fleet distributions

Abstract

The National Oceanic and Atmospheric Administration (NOAA) National Environmental, Satellite, Data, and Information Service (NESDIS) is conducting a two-year demonstration of Synthetic Aperture Radar (SAR) derived products called the Alaska SAR Demonstration (AKDEMO). This demonstration provides near real-time SAR data and derived products to the U.S. government community working in the waters near Alaska. One of these products is a constant false alarm rate (CFAR) vessel detection algorithm developed by Veridian ERIM International. This algorithm derives vessel positions from SAR data and delivers them within the context of the AKDEMO to users such as the U.S. Coast Guard, National Marine Fisheries Service, and the Alaska Department of Fish & Game (ADF&G), for management and regulatory purposes. The ScanSAR Wide B mode on RADARSAT-1 has an image swath width of 480 km, which covers a much larger area than is practical from ship, aircraft, and helicopter platforms. During the AKDEMO, SAR swaths are taken up to twice a day in both the Bering Sea and the Gulf of Alaska. During events such as fishery openings, extra data are also collected. A validation of the CFAR algorithm is presented using RADARSAT-1 SAR data along with ship fleet locations and sizes collected by the ADF&G at times nearly coincident with the SAR data.