An information fusion algorithm for data association in multitarget tracking

We employ the technique of uncertain information processing to solve problems of multitarget tracking. We consider the data association problem as a fuzzy partition. Dempster-Shafer theory is used to evaluate the plausibilities of the association events. Using the plausibilities, a fuzzy partition is performed. The grade of membership is then used as the weight of data association. A radar and a passive sonar tracking of two crossing targets are studied through computer simulation respectively. The results show that the Dempster Shafer theory based approach has an excellent ability to track multiple targets and has less complexity of the computation than the JPDAs.