Paper
19 May 2006 Surveillance radar range-bearing centroid processing, part II: merged measurements
Benjamin J. Slocumb, Daniel L. Macumber
Author Affiliations +
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.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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KEYWORDS
Expectation maximization algorithms

Radar

Detection and tracking algorithms

Surveillance

Target detection

Antennas

Algorithm development

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