Paper
7 August 2002 Multiple frame cluster tracking
Sabino Gadaleta, Mike Klusman, Aubrey Poore, Benjamin J. Slocumb
Author Affiliations +
Abstract
Tracking large number of closely spaced objects is a challenging problem for any tracking system. In missile defense systems, countermeasures in the form of debris, chaff, spent fuel, and balloons can overwhelm tracking systems that track only individual objects. Thus, tracking these groups or clusters of objects followed by transitions to individual object tracking (if and when individual objects separate from the groups) is a necessary capability for a robust and real-time tracking system. The objectives of this paper are to describe the group tracking problem in the context of multiple frame target tracking and to formulate a general assignment problem for the multiple frame cluster/group tracking problem. The proposed approach forms multiple clustering hypotheses on each frame of data and base individual frame clustering decisions on the information from multiple frames of data in much the same way that MFA or MHT work for individual object tracking. The formulation of the assignment problem for resolved object tracking and candidate clustering methods for use in multiple frame cluster tracking are briefly reviewed. Then, three different formulations are presented for the combination of multiple clustering hypotheses on each frame of data and the multiple frame assignments of clusters between frames.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sabino Gadaleta, Mike Klusman, Aubrey Poore, and Benjamin J. Slocumb "Multiple frame cluster tracking", Proc. SPIE 4728, Signal and Data Processing of Small Targets 2002, (7 August 2002); https://doi.org/10.1117/12.478511
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CITATIONS
Cited by 8 scholarly publications.
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KEYWORDS
Expectation maximization algorithms

Data modeling

Detection and tracking algorithms

Sensors

Missiles

Algorithm development

Target detection

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