Comparison of Spectral Estimation Methods for Rapidly Varying Currents Obtained by High-Frequency Radar

A comparative study of the periodogram method and high-resolution techniques (the autoregressive and multiple signal classification methods) for current mapping by a high-frequency (HF) surface wave radar is undertaken for the case of 66-s-long data. This analysis is extended from a previous study that used the commonly adopted 6-13-min coherent integration times. This reduction in the sample size will result in poor Doppler resolution and reduction in signal-to-noise ratio (SNR) for the conventional periodogram method. Two Bragg-peak identification methods for current estimation, the conventional centroid method and the symmetric-peak-sum (SPS) method, are examined in conjunction with each of the spectral estimation techniques. A weighted sum of the current estimates using the two Doppler shift identification methods is also recommended to provide a lower root mean square (RMS) difference. The weight is optimized using a genetic algorithm. Field data comparison with current measurements obtained from a current meter indicates that the high-resolution spectral estimation method is capable of providing the same RMS difference level for short and long time series, while the RMS difference for currents obtained from the periodogram method increases dramatically for short time series. Significant improvement in the current velocities retrieved from a short time series indicates the potential for measuring rapidly changing currents using the suggested technique.