Evaluation of the use of the modified-covariance method in HF radar ocean measurement

High-frequency (HF) radar systems are currently used to collect wave and current data. By applying the fast Fourier transform (FFT) method to the radar backscatter from the ocean surface, the Doppler spectrum is calculated, and from this the directional wave spectrum and wave parameter measurements are obtained. Because of the random nature of the ocean surface, spectral measurements are subject to random variability. To obtain stable estimates, each spectrum is calculated by averaging a number of FFT estimates. This method requires long data series, and problems may arise particularly in rapidly varying sea conditions. We consider the use of an alternative technique, the modified-covariance method, which can provide stable spectral estimates from short data sets. We show that the modified-covariance method with smaller data sets gives satisfactory results, comparable to those of the FFT method as usually applied, while the FFT method with smaller data sets performs poorly. Accurate wave parameter measurements are still obtained when the amount of data is reduced by a factor of four. The work suggests that an autoregressive model order of 30 and the use of 1500 data samples is sufficient for the accurate measurement of significant waveheight, mean period and wind direction.