Distributed MHT with active and passive sensors

This paper provides advances in distributed MHT. Our specific challenge is to provide a multi-sensor surveillance capability with disparate sensors: both active and passive sensors with widely varying clutter statistics, update rates, and coverage. Our first contribution is to develop a passive tracking capability that overcomes the lack of range observability with an effective use of virtual sensor measurements that provides efficiency, unbiased estimates, and consistent hypothesis scoring. Our second contribution is to enable high-performance fusion across active and passive sensors through equivalent-measurement processing. This has two benefits: equivalent measurements from passive data are sufficiently informative to score cross-sensor association hypotheses, and sensor update rates are made comparable across the network, thus simplifying downstream track fusion logic. We demonstrate the effectiveness of our distributed MHT solution with simulated air & ground targets in the context of Sense & Avoid for an unmanned aircraft with air and ground sensors.