SBIR-STTR Award

An innovative approach to updating theoreticalmodel-predicted directional wave spectra using real-time and artificial intelligence concepts is proposed. Current numerical wave forecast models do not utilize real-time measurements from ship reports, wave buoys and satellite remote sensing data as inputs to update its forecast. The proposed research will develop a coherent methodology to recreate directional wave spectra base don aggregate or imperfect measurements for updating model predicte ddirectional wave spectra.The potential commercial application as described by the awardee:The result of this project can potentially improve the accuracy of NOAA and Navy's operational wave model. In the long term, the proposed effort will lay the ground work for utilizing the data generated by the environmental satellite systems in the 1990's.

___(NOTE: Note: no official Abstract exists of this Phase II projects. Abstract is modified by idi from relevant Phase I data. The specific Phase II work statement and objectives may differ)___ An innovative approach to updating theoreticalmodel-predicted directional wave spectra using real-time and artificial intelligence concepts is proposed. Current numerical wave forecast models do not utilize real-time measurements from ship reports, wave buoys and satellite remote sensing data as inputs to update its forecast. The proposed research will develop a coherent methodology to recreate directional wave spectra base don aggregate or imperfect measurements for updating model predicte ddirectional wave spectra.The potential commercial application as described by the awardee:The result of this project can potentially improve the accuracy of NOAA and Navy's operational wave model. In the long term, the proposed effort will lay the ground work for utilizing the data generated by the environmental satellite systems in the 1990's.