Pattern classification approach to underwater acoustic communications based on the Wigner-Ville distribution

Abstract

This paper describes an approach and preliminary results associated with the use of pattern recognition techniques to identify transmitted information (symbols) in a temporally variant acoustic channel. The method allows the observation of the transmitted signal simultaneously in both time and frequency space and does not necessarily rely on the application of adaptive algorithms for reception. The observation of the symbol energy from the Wigner-Ville Distribution as two-dimensional pattern can allow the determination of channel characteristics over short symbol sequences and can provide a means for symbol detection. For the QPSK modulation used, wavelet filtering provides a basis for noise reduction and WVD cross tem separation. The process used for development of the pattern classifier is described and results are presented for shallow water acoustic data on a limited data set.