title: Object classification and acoustic imaging with active sonar.
abstract: The theoretical underpinnings of underwater acoustic classification and imaging using high-frequency active sonar are studied. All essential components of practical classification systems are incorporated in a Bayesian theoretic framework. The optimum decision rules and array processing are presented and evaluated. A systematic performance evaluation methodology is derived. New results quantify the relationship between classifier performance and object geometry, acoustic imaging, and the accuracy of a priori knowledge infused into the processor.
authors.affiliation: Naval Underwater Systems Center, Newport, Rhode Island 02841.
authors.forename: J G
authors.initials: JG
authors.lastname: Kelly
authors.forename: R N
authors.initials: RN
authors.lastname: Carpenter
authors.forename: J A
authors.initials: JA
authors.lastname: Tague
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D006801:Humans; D015233:Models, Statistical; D016011:Normal Distribution; D012542:Scattering, Radiation; D014465:Ultrasonics