Application of MHT to group-to-object tracking
Michael A. Kovacich, Tom Casaletto, William E. Lutjens, David D. McIntyre, Ralph Ansell, Ed VanDyk · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1991
This paper analyzes the performance of a version of the multiple hypothesis tracking concept applied to the group-to-object tracking problem for a pair of passive, scanning, space-based sensors. Group-to-object tracking is the process of tracking clusters of unresolved or nearly resolved objects as a group and then when individual objects become clearly resolved, tracking each object separately. An n scan back MHT algorithm, based on the work by Reid, is used to manage the scan-to-scan association process. It uses the A* search algorithm to find the best hypothesis and its statistically equivalent neighbors, based on their likelihood scores. An analysis is made of the performance and cost of the algorithm as a function of key algorithm parameters.