Three-dimensional source tracking in an uncertain environment via Bayesian marginalization.
This paper develops a non-linear Bayesian marginalization approach for three-dimensional source tracking in shallow water with uncertain environmental properties. The algorithm integrates the posterior probability density via a combination of Metropolis-Hastings sampling over environmental and bearing model parameters and Gibbs sampling over source range/depth, with track constraints on source velocity applied. Marginal distributions for source range/depth and source bearing are derived, with source position uncertainties estimated from the distributions. The Viterbi algorithm is applied to obtain the most probable three-dimensional track. The approach is applied to experimental narrowband data recorded on a bottom-moored horizontal line array in the Barents Sea.
Tollefsen
Dag
D
Norwegian Defence Research Establishment FFI, Box 115, 3191 Horten, Norway. dag.tollefsen@ffi.no
Dosso
Stan E
SE
D000162:Acoustics; D000465:Algorithms; D001499:Bayes Theorem; D021621:Imaging, Three-Dimensional; D009038:Motion; D009624:Noise, Transportation; D017711:Nonlinear Dynamics; D009792:Oceans and Seas; D012623:Seawater; D012767:Ships; D012815:Signal Processing, Computer-Assisted; D013016:Sound; D013018:Sound Spectrography; D013997:Time Factors