Bayesian tracking of two possibly unresolved maneuvering targets

The paper studies the problem of maintaining tracks of two targets that may maneuver in and out formation flight, whereas the sensor and measurement extraction chain produces false and possibly unresolved or missing measurements. If the possibility of unresolved measurements is not modelled then it is quite likely that either the two tracks coalesce or that one of the two tracks diverges on false measurements. In literature a robust measurement resolution model has been incorporated within an interacting multiple model/multiple hypothesis tracking (IMM/MHT) track maintenance setting. A straightforward incorporation of the same model within an IMM and probabilistic data association (PDA)-like hypothesis merging approach suffers from track coalescence. In order to improve this situation, the paper develops a track-coalescence avoiding hypotheses merging version for the two target problem considered. Through Monte Carlo simulations, the novel filters are compared with applying hypotheses merging approaches that ignore the possibility of unresolved measurements or track-coalescence.