Estimating Waveforms of Ocean Waves to Enhance the Efficiency of Ocean Energy Conversion

Advances in the area of active controls for wave energy converter (WEC) devices have uncovered a need for accurate estimates of the actual waves that will arrive at the WEC devices in the near future, typically several seconds ahead. This paper considers the parametric estimation of these impending waves by employing a network of spatially distributed ocean sensors, possibly of different types, whose measurements are noisy. We provide general expressions for the Fisher information matrix and the Cramer-Rao Bound (CRB) under white Gaussian noise. The CRB is a lower bound on the smallest mean-square estimation error, which is nearly achievable for a sufficient number of observations. The expressions are general in the sense that the sensor network could be made up of a single or multiple types of sensors. We present a low-complexity estimation method that employs linear optimizations coupled with periodograms and phase unwrapping. Numerical results demonstrating the accuracy of the presented estimation method relative to the CRB are provided.