Marine Vessels Acoustic Radiated Noise Classification in Passive Sonar Using Probabilistic Neural Network and Spectral Features

Abstract

Abstract Development of intelligent systems for classifying marine vessels based on their acoustic radiated noise is of major importance in the sonar systems. This paper focuses on three topics. The fast topic is applying some modifications to the conventional Probabilistic Neural Network (PNN), as a common classifier in supervised pattern recognition, and suggesting a new configuration of PNN which we call it, Multi-Spread Probabilistic Neural Network (MSPNN). The second topic is proposing a method for estimating the required spread values of MSPNN from training data. The third topic is introducing discriminating features which can be used for ship noise classification. These features are: the poles of autoregressive (AR) model with proper order, the coefficients of AR model with proper order and six features which are directly extracted from Power Spectral Density (PSD) of acoustic radiated noise of marine vessels. The performance of the conventional PNN and the suggested multi-spread PNN in classifying...