Predicting sea waves in the presence of pink noise

Abstract

It has been shown that the power output of some wave energy converters can be greatly increased if they respond to very short-term predictions of the shapes of the waves. Observations of sea waves are traditionally made using buoys carrying GPS and accelerometers. The recent development of low-cost MEMS devices has led to cheaper devices, but also to a renewed interest in the effects of pink (1=f ) noise and signal processing methods for mitigating its effects. Bandpass filtering reduces the effects of this noise, but its remaining influence disrupts, in particular, the phase of the signal, which has significant consequences for prediction. We introduce a Bayesian model that promotes the smooth theoretical spectral shapes of the signal and the pink noise and estimates the true signal from one or more sets of observations recorded in parallel. The signal we are aiming to discover is the profile of sea waves at a fixed location; the spectral shape is determined by the Pierson- Moskowitz model. We demonstrate the model on synthetic data and give some preliminary results for the prediction of real sea waves