Identification of underwater acoustic noise

The automatic recognition of noise situations in an underwater environment is an interesting issue, especially in coastal waters. In fact, recognition of ships by their acoustic signature captured by passive sonars can be very useful for automatic statistic tasks. This is a complex problem involving a large amount of signals with unstable characteristics. To achieve our goal, an artificial intelligence based approach was adopted in order to extract results from such large amounts of data. Traditional machine learning and neural network techniques were used and compared in their performance to select a technology able to produce a good classifier. Based on the neural network technology, a real-time classifier, using low cost hardware was developed. >