Surveillance radar range-bearing centroid processing, part II: merged measurements

Benjamin J. Slocumb; Daniel L. Macumber

doi:10.1117/12.673521

19 May 2006 Surveillance radar range-bearing centroid processing, part II: merged measurements

Benjamin J. Slocumb, Daniel L. Macumber

Proceedings Volume 6236, Signal and Data Processing of Small Targets 2006; 623604 (2006) https://doi.org/10.1117/12.673521
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

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.

Citation Download Citation

Benjamin J. Slocumb and Daniel L. Macumber "Surveillance radar range-bearing centroid processing, part II: merged measurements", Proc. SPIE 6236, Signal and Data Processing of Small Targets 2006, 623604 (19 May 2006); https://doi.org/10.1117/12.673521

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