Abstract
Many maritime operations can benefit from short-term deterministic sea wave prediction (DSWP). Conventional X-band radars constitute a convenient cheap source of measurements for DSWP. The radar backscatter measurements suffer from several imperfections such as the effect of larger waves shadowing smaller waves. In order to extract the wave profiles and build a reliable sea prediction model, multiple radar scans must be processed. In this paper, we present a new single-wavenumber least-squares spectral algorithm for wave prediction from radar backscatter. The proposed technique is evaluated using field data from a dedicated sea trial.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/g0ejshY_nhc
Highlights
deterministic sea wave prediction (DSWP) is a new branch of maritime science that aims at providing the sea shape in the vicinity of costal/offshore structure and floating vessels several tens of seconds ahead
Other successful DSWP algorithms overcome these limitations by solving a set of linear equations to obtain the relative spectral coefficients simultaneously, but they suffer from other problems such as poor-condition number and increased computational cost
The present work extends the algorithm to multiple scans in a sliding window fashion to improve the prediction model accuracy and reduce computational cost, and tests the results on backscatter data from a dedicated sea trial
Summary
DSWP is a new branch of maritime science that aims at providing the sea shape in the vicinity of costal/offshore structure and floating vessels several tens of seconds ahead. DSWP can identify the occurrence of quiescent waves periods that can be exploited to safely carry out wave limited tasks in sea conditions that based upon sea state statistics alone would be deemed unsafe (Al-Ani et al, 2019a; Al-Ani and Belmont, 2020). A commercially available wave profiling radar has been built based on this approach.
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