This paper describes a suite of target cueing algorithms which has been developed for the recognition of ship targets in the open ocean through FLIR Imagery. Imaging prepro cessing is first used to remove pattern and temporal noise. A relaxation technique is implemented to extract the target's silhouette. The superstructure profile is then obtained and classification is performed based on low-order coefficients of the discrete Fourier transform of the profile. This classification approach was found to have a 93% accuracy for short ranges (7-11 miles) and 70% accuracy for long ranges (11-20 miles) for eight target classes tested against 11398 images. Finally, a terminal homing algo rithm is described which incorporates scene tracking for maintaining track on a selected aimpoint which demonstrates superior performance over more conventional approaches.