
Proceedings Paper
Probabilistic track-to-track associationFormat | Member Price | Non-Member Price |
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Paper Abstract
We consider the track-to-track association problem. This problem is often a key ingredient when seeking to integrate data from multiple sensors. We propose a probabilistic approach, inspired by the joint probabilistic data association, or JPDA, approach used in the data association problem. To solve the proposed model we adapt a recent deterministic polynomial-time approximation algorithm. We give consideration also to the setting in which one or more sensors may contain biases.
Paper Details
Date Published: 21 May 2015
PDF: 8 pages
Proc. SPIE 9474, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIV, 94740B (21 May 2015); doi: 10.1117/12.2177206
Published in SPIE Proceedings Vol. 9474:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXIV
Ivan Kadar, Editor(s)
PDF: 8 pages
Proc. SPIE 9474, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIV, 94740B (21 May 2015); doi: 10.1117/12.2177206
Show Author Affiliations
Tim Zajic, Raytheon Integrated Defense Systems (United States)
Published in SPIE Proceedings Vol. 9474:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXIV
Ivan Kadar, Editor(s)
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