An ML-MHT approach to tracking dim targets in large sensor networks

Poor individual sensor performance as well as a large number of sensor scans per time interval are two challenges for multi-target tracking is large sensor networks. We introduce a two-stage processing scheme (ML-MHT) to address the former issue, and another to address the latter issue (MHT²). We consider as well the combination of these two techniques (ML-MHT²). Simulation results are encouraging. Future work will include application of these techniques to more challenging multi-sensor datasets characterized by extremely poor detection and localization performance.