Detection and classification of infrared decoys and small targets in a sea background

A combination of algorithms has been developed for the detection, tracking, and classification of targets at sea. In a flexible software setup, different methods of preprocessing and detection can be chosen for the processing of infrared and visible-light images. Two projects, in which the software is used, are discussed. In the SURFER project, the algorithms are used for the detection and classification of small targets, e.g., swimmers, dinghies, speedboats, and floating mines. Different detection methods are applied to recorded data. We will present a method to describe the background by fitting continuous functions to the data, and show that this provides a better separation between objects and clutter. The detection of targets using electro- optical systems is one part of this project, in which also algorithms for fusion of electro-optical data with radar data are being developed. In the second project, a simple infrared image-seeker has been built that is used to test the effectiveness of infrared decoys launched from a ship. In a more complicated image seeker algorithm, features such as contrast and size and characterization of trajectory are used to differentiate between ship, infrared decoys and false alarms resulting from clutter. In this paper, results for the detection of small targets in a sea background are shown for a number of detection methods. Further, a description is given of the simulator imaging seeker, and some results of the imaging seeker software applied to simulated and recorded data will be shown.