A comparison of Semi-Greedy multiple hypothesis methods in the radar data association problem

This paper shows the results of two different methods of implementing the semi-greedy auction algorithm for hypothesis selection in the multiple hypothesis radar data association problem. The goal is to compare the Semi-Greedy Track Selection (SGTS) technique proposed by Waard, Capponi et. al. to a traditional semi-greedy approach [2], [3], [4], [5], [6], [12]. This study uses detection data generated by a medium-fidelity digital simulation of targets and sensors passed through the developed multiple hypothesis system. The results show that there is a crossover point at 8 solution sets for simplistic scenarios and a crossover point of 3 solution sets for more complex scenarios. This result would suggest that implementations where more than 8 solution sets in the semi-greedy approach are to be considered, the traditional semi-greedy approach is favorable. In problems where less than 3 solution sets are to be considered, the SGTS method provides better performance.