TARGET CLASSIFICATION WITH OVERLAPPING WINDOW INTEGRATION USING WIGNER VILLE TRANSFORM

Abstract

In this study, automatic target classification was performed using underwater acoustic signals. Targets of underwater and surface ships were detected from long distances and classified using a signal integration algorithm with Wigner-Ville distribution for analyzing their noise. The proposed method exhibits an innovative approach by using Wigner-Ville distribution for signal integration and providing early detection and diagnosis compared to existing methods. Additionally, the Wigner-Ville distribution provides better discriminative features by separating frequency lines of targets from background noise with signal integration, which is observed as a new approach. With this proposed approach, it has been demonstrated that target classification performance improves.