Using PMHT for separation point estimation

Target tracking is limited by the resolution of the sensors providing the measurements. If two objects are in close proximity, they will return just one measurement in most instances. When these two objects separate enough to return two distinct measurements, the question then is: where did the objects actually separate? The actual separation point may be of interest and finding that separation point is the topic of this paper. Using the Probabilistic Multi-Hypothesis Tracking (PMHT) algorithm allows measurements to be "shared" between tracks, and therefore makes an excellent algorithm when there are closely-spaced unresolved measurements. In this paper, we will give an overview of how we apply the PMHT algorithm to this separation estimation problem, and then we apply the algorithm to two aircraft flying in formation and then separating. The results are obtained from a high-fidelity simulation environment and provide a good test for this developing approach.