Robust Passive and Active Track Fusion in a Distributed and Decentralized Architecture

This proposal addresses the problem of angle-only tracking of multiple jammer strobes in 3D by a distributed network of passive sensors with decentralized track processing. The challenges are (1) to develop robust algorithms for signal and/or data processing to associate measurements unambiguously from one sensor to others in the network (that is, “deghost” the possible intersections of jammer strobes), (2) to associate and track for various sensor/target geometries, (3) to be insensitive to data timeliness, and (4) to transition to single-unit tracking where feasible. We propose to develop robust algorithms and software by leveraging on Toyon’s existing multiple-hypothesis tracking (MHT) framework for 3D passive tracking and fusion of passive tracks in a distributed sensor network. For the passive tracking problem, we shall develop range-parameterized extended Kalman filter algorithms and software in MHT using the modified spherical polar coordinates (MSC). We shall add a number dynamic models using the MSC to the interacting multiple model component of MHT to handle maneuvering targets. Initially, we shall demonstrate track-to-track fusion of active and passive tracks using the convex combination algorithm and information filter.