Improved Active Sonar Tracking in Clutter Using Integrated Feature Data

Target tracking has traditionally focused on the use of kinematic information, such as bearing, range, position, or speed. In some cases, it is possible to extract additional target information that may be useful in the maintenance of reliable tracks, or the establishment of target type or identity. Several methods have been proposed for the use of feature information in target tracking. In this paper, we discuss and evaluate its use as a component of the cumulative likelihood ratio used for track management and contact assignment in a track-oriented multihypothesis tracker (MHT) using a sorted branch and bound approach to contact assignment. The active sonar sea trial data used in this evaluation, Clutter09, include feature values based on the perceptual capabilities of the human auditory system. Three measurement scenarios are considered. Comparisons between the baseline case, which used only kinematic information, and several feature-aided cases showed that the performance of the tracker improved noticeably when feature information was used. The MHT, which was working at a depth of six scans, was also able to tolerate seven times as many false contacts in the feature-aided cases as in the baseline cases. This corresponds to improved detection and tracking of targets that are weaker, or at greater range, or in a more cluttered environment. Results were also significantly better when compared with cases where the feature information was used to prefilter the contacts entering the tracker or to postfilter the tracks produced by the tracker.