title: Three-dimensional multiple-source focalization in an uncertain ocean environment.
abstract: This letter develops a Bayesian focalization approach for three-dimensional localization of an unknown number of sources in shallow water with uncertain environmental properties. The algorithm minimizes the Bayesian information criterion using adaptive hybrid optimization for environmental parameters, Metropolis sampling for source bearing, and Gibbs sampling for source ranges and depths. Maximum-likelihood expressions are used for unknown complex source strengths and noise variance, which allows these parameters to be sampled implicitly. An efficient scheme for adding/deleting sources is used during the optimization. A synthetic example considers localizing a quiet source in the presence of multiple interferers using a horizontal line array.
authors.affiliation: Norwegian Defence Research Establishment (FFI), Box 115, 3191 Horten, Norway dag.tollefsen@ffi.no.
authors.forename: Dag
authors.initials: D
authors.lastname: Tollefsen
authors.forename: Stan E
authors.initials: SE
authors.lastname: Dosso
mesh_terms: D000162:Acoustics / Q000295:instrumentation; D000465:Algorithms; D001499:Bayes Theorem; D003198:Computer Simulation; D004867:Equipment Design; D009038:Motion; D009791:Oceanography / Q000295:instrumentation / Q000379:methods*; D009792:Oceans and Seas; D011312:Pressure; D012815:Signal Processing, Computer-Assisted; D013016:Sound; D013018:Sound Spectrography; D013997:Time Factors; D014160:Transducers, Pressure; D035501:Uncertainty; D014867:Water
chemical_list: D014867:Water