Application of Signal Processing and Pattern Recognition to Underwater Acoustics

Abstract

This paper consists of four inter-related topics on the application of signal processing and pattern recognition to underwater acoustics. Part I is on pattern recognition processing for target motion analysis. The three-dimensional target motion analysis (TMA) in a multipath environment with bearing and multipath delay information has been examined and the extended Kalman filter was used to estimate the target parameters for localization and tracking of a moving underwater target. In this paper, pattern recognition is considered in the context of TMA. Two approaches are examined. The first approach uses the classification method and the pattern matching idea to identify the target location, without employing the conventional optimal filtering. The second approach uses the extended Kalman filtering but with initial parameters determined by the classification method. The simulation results clearly demonstrate a major improvement in the TMA capability via pattern-recognition processing.