Sonar Detection and Classification of Underwater UXO and Environmental Parameters

Abstract

Abstract : This report summarizes an effort carried out at the Naval Surface Warfare Center--Panama City Division (NSWC PCD) under SERDP funding to work towards resolving issues that affect sonar detection and classification/identification (C/ID) of underwater UXO using sonar. We leveraged on-going Navy sponsored sonar tests to collect data to further the model development and validation needed to keep sonar models and simulations such as PC SWAT and the more recent finite-element-based models up to date for UXO applications. This modeling capability and test data was then used both to build a database of sonar target signals useful for developing and evaluating C/ID algorithms that separate UXO from bottom clutter and to look for and understand target signatures that appear sufficiently unique for classification. While traditional C/ID based on target imaging remains an important tool, it is likely to be insufficient for small and/or buried UXO. Processing sonar target responses onto non-imaging spaces was investigated as a means to find physics-motivated clues like elastic wave signatures that don't require high resolution to provide high classification confidence. Classification analyses performed on target acoustic data collected in NSWC PCD's freshwater pond demonstrated the feasibility of class separating different targets using features derived from non-image representations of the target. Unlike image-based classification, this methodology was even shown capable of discriminating between targets of the same size and shape but different material composition.