Maximum likelihood probabilistic data association (ML-PDA) tracker implemented in delay/bearing space applied to multistatic sonar data sets

Steven Schoenecker; Peter Willett; Yaakov Bar-Shalom

doi:10.1117/12.918235

15 May 2012 Maximum likelihood probabilistic data association (ML-PDA) tracker implemented in delay/bearing space applied to multistatic sonar data sets

Steven Schoenecker, Peter Willett, Yaakov Bar-Shalom

Author Affiliations +

Proceedings Volume 8393, Signal and Data Processing of Small Targets 2012; 83930J (2012) https://doi.org/10.1117/12.918235
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

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.

Citation Download Citation

Steven Schoenecker, Peter Willett, and Yaakov Bar-Shalom "Maximum likelihood probabilistic data association (ML-PDA) tracker implemented in delay/bearing space applied to multistatic sonar data sets", Proc. SPIE 8393, Signal and Data Processing of Small Targets 2012, 83930J (15 May 2012); https://doi.org/10.1117/12.918235

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