Comparison of two MDA algorithms for a problem in missile defense
Javier Areta, Yaakov Bar‐Shalom, Mark Levedahl · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
In this paper we compare the performance of two Multidimensional Assignment Algorithms (MDA), the Lagrangean Relaxation based S-D algorithm and the Sequential m-best 2-D algorithm, applied to a realistic problem in missile defense surveillance. The benchmark problem consists of a set of sources that provide "event" (track) estimates of multiple launches, via a number of communication networks to a Fusion Center (FC) which has to perform data association prior to fusion. The network model used "loses" the information tag that distinguishes reports from the same source transmitted through different networks, i.e., the track identity (ID) assigned by the source is not passed on. Only a track ID assigned by the network, and the source ID accompany the track. Thus detection and elimination of track duplications at the FC is needed. The proposed hierarchical approach to the problem requires the solution of several MDA problems before calculating the fused estimate, so accuracy of the solution of each is crucial. Examples with several launches, sources and networks are presented to compare the performance of the two assignment algorithms.