Spectral Algorithm in Waves Profiling and Prediction From Radar Backscatter

Conventional X-band radars constitute a convenient cheap source of measurements for deterministic sea wave profiling and prediction. The radar backscatter measurements, however, suffer from several imperfections such as the effects of larger waves shadowing smaller waves. In order to extract the wave profiles and build a reliable (spectral) sea model, multiple radar scans must be processed. A technique based on 3DFFT has been proven to show promising results and has been implemented in commercially available wave profiling radars. Nonetheless, there are several drawbacks associated with using 3DFFT to determine the phase-resolved spectral coefficients in the sea model from a number of radar scans. In this article, we present an alternative spectral approach that can offer several advantages over 3DFFT in radar wave profiling and prediction. First, it has the ability to directly handle ship movement and radar rotation antenna effects with no approximation, interpolation, or extra cost. Second, it can offer an increase in the output update rate by eliminating repeating computations, which is achieved by its recursive nature (i.e., using past output) and by its multistep architecture. Third, it can be set to readily target the relative spectral components that can best describe the wave field. The proposed technique is evaluated using raw backscatter field data from a dedicated sea trial. A simulation study is also included to gain more understanding about the performance of the proposed technique in particular and radar wave sensing and prediction in general.