Signal processing, tracking, and resource allocation for highly maneuvering closely spaced targets

In this paper a novel signal processor combined with a tracker/radar resource allocator based on the Interacting Multiple Model Probabilistic Data Association (IMMPDA) estimator is presented for tracking highly maneuvering, closely spaced targets. An advanced monopulse processing technique, which uses the Maximum Likelihood (ML) approach and yields separate angle measurements for two targets in the same radar beam and same range cell, i.e., they are unresolved, is developed. This processing results in a significant improvement, in terms of tracking performance, over techniques using the monopulse ratio for the same problem. The standard monopulse ratio technique of extracting angles yields a single merged measurement when the targets are unresolved, resulting in track coalescence. The signal processor and tracker were coupled with a radar resource allocator to minimize the radar resources required to track the target while maintaining a low track loss and ensuring high estimation accuracies.