Abstract: In accordance with one aspect of the present invention, a system for tracking a target is provided that includes an image sensor mounted to a gimbal for acquiring an image, wherein the image includes a plurality of pixels representing the target and a background. The system further includes a motor for rotating the gimbal and an autotracker electrically coupled to the image sensor and the motor. The autotracker includes a probability map generator for computing a probability that each of the plurality of pixels having a particular intensity is either a portion of the target or a portion of the background, a pixel processor in communicative relation with the probability map generator for calculating a centroid of the target based upon the probabilities computed by the probability map generator, and a controller in communicative relation with the pixel processor for generating commands to the motor based upon the centroid.

Abstract: In accordance with one aspect of the present invention, a system for tracking a target is provided that includes an image sensor mounted to a gimbal for acquiring an image, wherein the image includes a plurality of pixels representing the target and a background. The system further includes a motor for rotating the gimbal and an autotracker electrically coupled to the image sensor and the motor. The autotracker includes a probability map generator for computing a probability that each of the plurality of pixels having a particular intensity is either a portion of the target or a portion of the background, a pixel processor in communicative relation with the probability map generator for calculating a centroid of the target based upon the probabilities computed by the probability map generator, and a controller in communicative relation with the pixel processor for generating commands to the motor based upon the centroid.

Abstract: An imaging target tracker and a method for determining thresholds that are used to optimally distinguish a target from background. The present invention is an imaging target tracker that comprises a likelihood-based threshold selection method that uses knowledge of the location of a target to build up temporally-smoothed grey-level distribution or likelihood maps. Inner and outer histograms are formed that comprise inner and outer regions of an image, respectively, using inner, buffer and outer gates that segment the image. The inner and outer histograms are then recursively smoothed. A lookup table of actually observed pixel values is formed. A target likelihood value for actually observed pixel values is then computed. Legal start and end points of histogram segments are identified. Valid histogram segments are identified. The longest histogram segment is identified. Finally, two optimal thresholds are selected 8 and are set at respective ends of histogram segments.

Abstract: A method for measuring and quantifying clutter, and target detection and tracking systems that employs wavelet-based clutter quantification to generate a clutter number and a signal-to-clutter ratio derived therefrom to achieve improved target detection performance. The method processes video signals representative of an image scene containing a target and background clutter to provide for more accurate tracking of the target by a tracker(s). The method comprises processing the video signals to compute a wavelet clutter number, processing the video signals to compute a signal-to clutter ratio using the wavelet clutter number, and generating a pointer to a lookup table that sets parameters and selects the tracker that is to be used to track the target based upon the computed signal-to clutter ratio.

Abstract: A tracking system and method that achieves system bandwidth reduction and analyzes scene information from an expanded area around a tracked target. Objects in the scene that may interfere with the target and cause degraded tracking performance are tracked to determine the level of likely perturbation of a primary tracker due to interference. The system predicts the time at which interference due to clutter objects will occur and the estimated time duration of the interference. The system uses this information to determine and variably adjust the gains of a track loop to prevent track loss while detecting and tracking maneuvers of the target.