Comparative Study of FDA and Time Series Approaches for Seabed Classification from Acoustic Curves

Abstract

Seabed classification in coastal environments is usually accomplished using multivariate methods applied to acoustic features from corrected or uncorrected echoes. This paper presents a comparative study of alternative statistical tools based on time series clustering and non-hierarchical clustering methods for functional data. This allows us to consider the entire acoustic signal without information reduction and assess performance using data acquired in a controlled environment with three different seabed types. The methods considered are used to both analyse the classification power of the recorded echoes and identify the most significant portions of signal.