Classification of SAR ship images with the aid of a syntactic pattern recognition algorithm. NASA STI/Recon

Synthetic Aperture Radar (SAR) systems have made possible the generation of radar images of ships with high enough resolution to allow numerous targets or scatterers to be visible. With the availability of numerous scatterers in one radar image, it is theoretically possible to identify the class of a ship. The SAR image of a ship is a function of the location of scatterers, the SAR system frequency, the radar-to-ship viewing angle, the amount and type of sea-induced ship motion, and the length of the aperture. Because of the dependence on these variables, the number of images representing any one ship is large. It is the job of a Radar Operator to study and understand the abundance of radar images that can be encountered, and attempt to make the correct classification. Fast classification response times are required, however, since these images would normally be acquired in a real-time scenario. As a result of the large number of images and the fast classification response required, some form of computer-based aid for the operator is justified. A Syntactic Patterr Recognition Algorithm (called the Coarse Feature Classifier (CFC)) has been developed to aid the Radar Operator in performing the task of classifyin