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Proceedings Paper

Surveillance radar range-bearing centroid processing, part II: merged measurements
Author(s): Benjamin J. Slocumb; Daniel L. Macumber
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Paper 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.

Paper Details

Date Published: 19 May 2006
PDF: 12 pages
Proc. SPIE 6236, Signal and Data Processing of Small Targets 2006, 623604 (19 May 2006); doi: 10.1117/12.673521
Show Author Affiliations
Benjamin J. Slocumb, Numerica Corp. (United States)
Daniel L. Macumber, Numerica Corp. (United States)

Published in SPIE Proceedings Vol. 6236:
Signal and Data Processing of Small Targets 2006
Oliver E. Drummond, Editor(s)

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