AUTOREGRESSIVE MODELING FOR OCEAN WAVE RADAR MODULATION TRANSFER-FUNCTION

The standard technique for computing ocean wave - radar modulation tra nsfer functions (MTFs) depends on nonparametric fast Fourier transform (FFT) methods. In this paper we suggest a new approach applying an au toregressive (AR) parametric spectral estimator. The analysis shows th at the two-channel autoregressive model produces smooth estimates of t he MTF and permits better frequency resolution than FFT techniques. Th e feed-across effect inherent in the methods developed to evaluate the multichannel AR coefficients causes a negligible effect on MTF. The A R-based MTF depends weakly on the record length; for steady meteorolog ical conditions the AR model of the MTF for a 2-min data run is compar able with ones calculated using 10 min or more of data. In the same si tuation the FFT technique is unreliable for records of less than 10 mi n. The appropriate order of the multichannel AR model can vary without causing significant change in the MTF. In most cases any order betwee n 8 and 16, depending on radar system parameters and meteorological co nditions, will give acceptable results.