Underwater ordnance classification using Time-Frequency signatures of backscattering signals

Abstract

This paper introduces a novel underwater target classification scheme which recognizes underwater ordnances based on their backscattered Time-Frequency (TF) signatures. The objective is to automatically identify the shape and interior content of sea-disposed underwater munitions and ordnance found in the Hawaiian coastlines. This effort helps in the removal of the above sea-disposals from the ocean floor. A dolphin Sonar is used to generate backscattering signals from the targets. Characteristics of different targets are studied using the Wigner-Ville Distribution (WVD), and are discriminated using a cluster-based classification scheme. This method was tested on the backscattered signals from dummy ordnance measured in a water tank.