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Proceedings Paper

Maximum likelihood probabilistic data association tracker applied to bistatic sonar data sets
Author(s): Steven Schoenecker; Peter Willett; Yaakov Bar-Shalom
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Paper Abstract

In the early 1990's, the Maximum Likelihood Probabilistic Data Association (ML-PDA) tracker was developed in a passive sonar framework, and subsequent research has shown it to be effective for tracking very low SNR targets. This was done with both active and passive sonar, for targets that have some given type of deterministic motion. Recent work has focused on applying ML-PDA to bistatic sonar data. Here, we apply ML-PDA in a sliding window implementation to three bistatic data sets used by the MSTWG (Multistatic Tracking Working Group): the SEABAR 2007 data set, the TNO Blind 2008 data set, and a new blind data set provided by Metron in 2009.

Paper Details

Date Published: 16 April 2010
PDF: 13 pages
Proc. SPIE 7698, Signal and Data Processing of Small Targets 2010, 76980K (16 April 2010); doi: 10.1117/12.850215
Show Author Affiliations
Steven Schoenecker, Naval Undersea Warfare Ctr. (United States)
Peter Willett, Univ. of Connecticut (United States)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)


Published in SPIE Proceedings Vol. 7698:
Signal and Data Processing of Small Targets 2010
Oliver E. Drummond, Editor(s)

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