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4 October 1999 K-near optimal solutions to improve data association in multiframe processing
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Abstract
The problem of data association remains central in multitarget, multisensor, and multiplatform tracking. Lagrangian relaxation methods have been shown to yield near optimal answers in real-time. The necessity of improvement in the quality of these solutions warrants a continuing interest in these methods. A partial branch-and-bound technique along with adequate branching and ordering rules are developed. Lagrangian relaxation is used as a branching method and as a method to calculate the lower bound for subproblems. The result shows that the branch-and-bound framework greatly improves the solutions in less time than relaxation alone.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Aubrey B. Poore and Xin Yan "K-near optimal solutions to improve data association in multiframe processing", Proc. SPIE 3809, Signal and Data Processing of Small Targets 1999, (4 October 1999); https://doi.org/10.1117/12.364041
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