Automatic ship recognition is of interest in such problems as over-the-horizon surface surveillance and targeting, long range air targeting, and satellite ocean surveillance. Our approach is model-driven. It uses the fact that the wake caused by a cruising ship has a higher temperature profile than the surrounding water background. In addition, we distinguish between the active wake and the turbulent water surrounding the ship. Furthermore, the temperature of the ship itself is usually lower than that of the ocean. Finally, we make use of the knowledge of ship sizes, convoy patterns and other information concerning ships traveling in formation. An image from a radiometric sensor forms the basis of the analysis. Edge detection and region association techniques are used to locate a "zone of activity", a region of the image that contains the ship. Grey level histogram analysis of the zone is then used to categorize pixels into "ship", "wake", and "water". Results of experiments using this technique are presented.