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Proceedings Paper

Maximum likelihood probabilistic data association (ML-PDA) tracker implemented in delay/bearing space applied to multistatic sonar data sets
Author(s): Steven Schoenecker; Peter Willett; Yaakov Bar-Shalom
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Paper Abstract

The Maximum Likelihood Probabilistic Data Association (ML-PDA) tracker is an algorithm that has been shown to work well against low-SNR targets in an active multistatic framework with multiple transmitters and multiple receivers. In this framework, measurements are usually received in time-bearing space. Prior work on ML-PDA implemented the algorithm in Cartesian measurement space - this involved converting the measurements and their associated covariances to (x, y) coordinates. The assumption was made that Gaussian measurement error distributions in time-bearing space could be reasonably approximated by transformed Gaussian error distributions in Cartesian space. However, for data with large measurement azimuthal uncertainties, this becomes a poor assumption. This work compares results from a previous study that applied ML-PDA in a Cartesian implementation to the Metron 2009 simulated dataset against ML-PDA applied to the same dataset but with the algorithm implemented in time-bearing space. In addition to the Metron dataset, a multistatic Monte Carlo simulator is used to create data with properties similar to that in the Metron dataset to statistically quantify the performance difference of ML-PDA operating in Cartesian measurement space against that of ML-PDA operating in time-bearing space.

Paper Details

Date Published: 15 May 2012
PDF: 14 pages
Proc. SPIE 8393, Signal and Data Processing of Small Targets 2012, 83930J (15 May 2012); doi: 10.1117/12.918235
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. 8393:
Signal and Data Processing of Small Targets 2012
Oliver E. Drummond; Richard D. Teichgraeber, Editor(s)

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