Paper
25 August 2004 Improved hypothesis selection for multiple hypothesis tracking
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Abstract
The need to track closely-spaced targets in clutter is essential in support of military operations. This paper presents a Multiple Hypothesis Tracking (MHT) algorithm which uses an efficient structure to represent the dependency which naturally arises between targets due to the joint observation process, and an Integral Square Error (ISE) mixture reduction algorithm for hypothesis control. The resulting algorithm, denoted MHT with ISE Reduction (MISER), is tested against performance metrics including track life, coalescence and track swap. The results demonstrate track life performance similar to that of ISE-based methods in the single-target case, and a significant improvement in track swap metric due to the preservation of correlation between targets. The result that correlation reduces the track life performance for formation targets requires further investigation, although it appears to demonstrate that the inherent coupling of dynamics noises for such problems eliminates much of the benefit of representing correlation only due to the joint observation process.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Juan R. Vasquez and Jason L. Williams "Improved hypothesis selection for multiple hypothesis tracking", Proc. SPIE 5428, Signal and Data Processing of Small Targets 2004, (25 August 2004); https://doi.org/10.1117/12.542065
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CITATIONS
Cited by 8 scholarly publications.
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KEYWORDS
Detection and tracking algorithms

Target detection

Modeling

Data modeling

Error analysis

Matrices

Target recognition

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