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Proceedings Paper

Using a multiple analytical distribution filter for underwater localization
Author(s): Dov Kruger; Hongyuan Shi; Yingying Chen; Hongbo Liu; Jie Yang; Len Imas
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Paper Abstract

This paper presents a high efficiency algorithm, Multiple Analytical Distribution Filter (MADF), to estimate location for underwater navigation. Using small grid sampling around candidate areas of high probability, MADF computes probabilities directly from the known analytical distributions of each beacon. The algorithm is deterministic and achieves similar results to particle filters, but at a lower computational cost in our tests. MADF and particle filters represent improvements over Kalman Filters for environments characterized by non-Gaussian noise distribution.

Paper Details

Date Published: 25 September 2009
PDF: 8 pages
Proc. SPIE 7480, Unmanned/Unattended Sensors and Sensor Networks VI, 74800T (25 September 2009); doi: 10.1117/12.834893
Show Author Affiliations
Dov Kruger, Stevens Institute of Technology (United States)
Hongyuan Shi, Stevens Institute of Technology (United States)
Yingying Chen, Stevens Institute of Technology (United States)
Hongbo Liu, Stevens Institute of Technology (United States)
Jie Yang, Stevens Institute of Technology (United States)
Len Imas, Stevens Institute of Technology (United States)


Published in SPIE Proceedings Vol. 7480:
Unmanned/Unattended Sensors and Sensor Networks VI
Edward M. Carapezza, Editor(s)

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