IMMPDAF Solution for the Tracking and Radar Management Benchmark with Merged Measurements and Multipath

摘要

Radar signal processing is a key part in tracking closely spaced targets and targets in the presence of sea-surface-induced multipath. These issues are the salient features of the benchmark problem for tracking unresolved targets combined with radar management, for which this paper presents the only complete solution to date. In this paper a modified version of a recently developed "superresolution" maximum likelihood (ML) angle estimator for closely spaced targets as well as targets in the presence of multipath are presented. Efficient radar resource allocation algorithms for two closely spaced targets and targets flying close to the sea surface are also presented. Finally, the IMMPDAF (interacting multiple model estimator with probabilistic data association filter modules) is used to track these targets. It is found that a two-model IMMPDAF performs better than the three model version used in the previous benchmark. Also, the IMMPDAF with a coordinated turn model works better than the one using a Wiener process acceleration model. The signal processing and tracking algorithms presented here, operating in a feedback manner, form a comprehensive solution to the most realistic tracking and radar management problem to date.