Sea floor recognition with bio-inspired echolocation

This paper presents a study of different feature extraction methods for sea floor recognition. This analysis is based on the frequency components of the return signals from a bio-inspired wideband sonar. Part of the sea floor of Tallinn Bay was surveyed using a wideband sonar with linear chirp pulses. The area contains citadel constructions and sediment regions. The recognition task is to distinguish between these two types of the sea floor. It was observed that the frequency spectrum of the signals returned from these two surfaces has different distributions. The work presents three frequency based approaches for the feature extraction process: Time-Frequency Moment Singular Value Decomposition (tFM-SVD), Energy Vector and Complete Frequency Spectrum. Comparison of the techniques is made in terms of the classification results.