Tracking separating targets with a monopulse radar: idealized resolution

The tracking of separating objects with a monopulse radar is a particularly challenging problem in that the presence of merged measurements result in significant delays in the initiation of tracks on the new objects. Furthermore, the unknown inflation in the variance and the bias of the angle-of-arrival estimates result in extra tracks and hinders track continuity. This paper presents an algorithm for tracking separating objects with a monopulse radar. The algorithm combines a Neyman-Pearson hypothesis test for detecting merged measurements, a method of parsing merged measurements into two angle-of-arrival estimates, and a track initiation procedure that takes advantage of the parsed measurements. The new algorithm was implemented in a sophisticated computer simulation environment to evaluate the performance improvements provided by the new algorithm. The output of the simulation environment is used to illustrate the challenges associated with tracking separating objects with a monopulse radar.