A fast method for finding the exact N-best hypotheses for multitarget tracking

The necessity for multiple hypothesis tracking (MHT) is recognized throughout the SDI tracking community. However, implementations of MHT techniques have required enormous amounts of computer time and memory. An efficient method of measurement-to-target association that makes MHT practical for the first time is presented. The method finds the exact N-best feasible hypotheses directly from a sequence of linear assignment problem solutions. >