Maximum likelihood probabilistic data association tracker applied to bistatic sonar data sets

Steven Schoenecker; Peter Willett; Yaakov Bar-Shalom

doi:10.1117/12.850215

15 April 2010 Maximum likelihood probabilistic data association tracker applied to bistatic sonar data sets

Steven Schoenecker, Peter Willett, Yaakov Bar-Shalom

Proceedings Volume 7698, Signal and Data Processing of Small Targets 2010; 76980K (2010) https://doi.org/10.1117/12.850215
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

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.

Citation Download Citation

Steven Schoenecker, Peter Willett, and Yaakov Bar-Shalom "Maximum likelihood probabilistic data association tracker applied to bistatic sonar data sets", Proc. SPIE 7698, Signal and Data Processing of Small Targets 2010, 76980K (15 April 2010); https://doi.org/10.1117/12.850215

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