Paper
16 September 2011 Improved multiframe association for tracking maneuvering targets
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Abstract
Data association is the crucial part of any multitarget tracking algorithm in a scenario with multiple closely spaced targets, low probability of detection and high false alarm rate. Multiframe assignment, which solves the data association problem as a constrained optimization, is one of the widely accepted methods to handle the measurement origin uncertainty. If the targets do not maneuver, then multiframe assignment with one or two frames will be enough to find the correct data association. However, more frames must be considered in the data association for maneuvering targets. Also, a target maneuver might be hard to detect when maneuvering index, which is the function of sampling time, is small. In this paper, we propose an improved multiframe data association with better cost calculation using backward multiple model recursion, which increases the maneuvering index. The effectiveness of the proposed algorithm is demonstrated with simulated data.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Biruk K. Habtemariam, R. Tharmarasa, N. Nandakumaran, M. McDonald, and T. Kirubarajan "Improved multiframe association for tracking maneuvering targets", Proc. SPIE 8137, Signal and Data Processing of Small Targets 2011, 81370O (16 September 2011); https://doi.org/10.1117/12.896465
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Cited by 1 scholarly publication.
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KEYWORDS
Target detection

Data modeling

Detection and tracking algorithms

Motion models

Algorithm development

Motion estimation

Computer simulations

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