Paper
15 May 2012 H-PMHT for correlated targets
Author Affiliations +
Abstract
The Histogram Probabilistic Multi-Hypothesis Tracker (H-PMHT) is a parametric track-before-detect algorithm that has been shown to give good performance at a relatively low computation cost. Recent research has extended the algorithm to allow it to estimate the signature of targets in the sensor image. This paper shows how this approach can be adapted to address the problem of group target tracking where the motion of several targets is correlated. The group structure is treated as the target signature, resulting in a two-tiered estimator for the group bulk-state and group element relative position.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Samuel J. Davey, Monika Wieneke, and Neil J. Gordon "H-PMHT for correlated targets", Proc. SPIE 8393, Signal and Data Processing of Small Targets 2012, 83930R (15 May 2012); https://doi.org/10.1117/12.919511
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CITATIONS
Cited by 7 scholarly publications.
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KEYWORDS
Image sensors

Detection and tracking algorithms

Sensors

Motion models

Expectation maximization algorithms

Image processing

Process modeling

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