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It is widely accepted that Classification Aided Tracking (CAT) has the potential to maintain continuous tracks on important targets. Moreover, when augmented with target behavior, a joint tracking and ID system can enhance the data association process for ground tracking systems. It is also recognized that it is likely that some targets in any scenario may not be included in a database, and the presence of such confusers would diminish both tracking and ID performance. Moreover, even with ID information, tracks may switch targets. Thus, a joint tracking and identification architecture has been developed which addresses the issues of both confusers and track ID switching. These methods are being tested using simulated dynamic ground targets and radar High Range Resolution (HRR) data provided by the Moving and Stationary Target Acquisition and Recognition (MSTAR) project.
The paper begins by giving an overview of the IMM/MHT tracker that has been designed to handle the unique characteristics (such as on-off road behavior) of the ground target tracking problem. Then, a joint tracking identification methodology is described. Implementing this approach, target behavior (such as being part of a group, speed, and on/off road motion) can be used both in the data association and for target type information. A Dempster-Shafer method is used for combining all classification-related data. In addition, confusers are taken into account by incorporating the information from targets that are in the database. The track score, required in all MHT data association decisions, is augmented with a feature-related term derived from the conflict term computed from an application of Dempster's Rule. The histories of the most likely ID for each track are checked to identify possible switches, and if tracks are believed to have switched IDs, then the state and the covariances of these tracks are exchanged so that future observations may be consistent with the original targets. Finally, the paper illustrates the proposed methods using results from a detailed simulation of target convoys, with and without confuser targets, that perform on and off road maneuvers. Results using MSTAR HRR data are presented for Classification-Aided (CAT) approaches to feature-aided tracking.
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