Accession Number : ADA280589
Title : Autonomous Sonar Classification Using Expert Systems,
Corporate Author : NAVAL POSTGRADUATE SCHOOL MONTEREY CA DEPT OF COMPUTER SCIENCE
Personal Author(s) : Brutzman, Donald P. ; Compton, Mark A. ; Kanayama, Yutaka
Report Date : JUN 1992
Pagination or Media Count : 11
Abstract : An expert system can process active sonar returns, perform geometric analysis and autonomously classify detected underwater objects. Autonomous classification of objects is an essential requirement for independent operation by autonomous underwater vehicles (AUVs). Most AUVs are only capable of rudimentary sensor analysis, since standard approaches to evaluation and classification of sonar data require excessive signal processing and computational power to be practical. This paper describes how to develop an autonomous sonar classification expert system for a working AUV. A fundamental approach is presented for applying geometric reasoning and expert system heuristics to sonar classification. Preliminary sonar processing is performed using parametric regression line fitting. A polyhedron-building algorithm correlates the parametric regression line segments into geometric objects. After quantifying geometric object attributes, objects are classified using rule-based evaluation of quantitative and qualitative attributes combined with sonar classification heuristics.
Descriptors : *UNDERWATER VEHICLES, *SONAR EQUIPMENT, *UNDERWATER NAVIGATION, ALGORITHMS, APPROACH, BUILDINGS, CLASSIFICATION, EXPERT SYSTEMS, FITTINGS, OPERATION, PAPER, POWER, PROCESSING, REASONING, REQUIREMENTS, SIGNAL PROCESSING, SIGNALS, SONAR, STANDARDS, UNDERWATER, UNDERWATER OBJECTS, VEHICLES.
Subject Categories : Acoustic Detection and Detectors
Underwater and Marine Navigation and Guidance
Distribution Statement : APPROVED FOR PUBLIC RELEASE