Surveillance radar range-bearing centroid processing, part II: merged measurements
Benjamin J. Slocumb, Daniel L. Macumber · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
In non-monopulse mechanically scanned surveillance radars, each target can be detected multiple times as the beam is scanned across the target. To prevent redundant reports of the object, a centroid processing algorithm is used to associate and fuse multiple detections, called primitives, into a single object measurement. At the 2001 SPIE conference,1 Part I of this paper was presented wherein a new recursive least squares algorithm was derived that produces a single range-bearing centroid estimate. In this Part II paper, the problem is revisited to address one important aspect not previously considered. We develop a new algorithm component that will parse merged measurements that result from the presence of closely-spaced targets. The technique uses tracker feedback to identify the number of constituents in which to decompose the identified merged measurement. The algorithm has two components: one is a decomposition group formation algorithm, and the second is the expectation-maximization based centroid decomposition algorithm. Simulation results are presented that show the algorithm improves tracker completeness as well as measurement accuracy in scenarios with closely spaced objects.