Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Wind Direction Estimation From Rain-Contaminated Marine Radar Data Using the Ensemble Empirical Mode Decomposition Method
Two ensemble empirical mode decomposition (EEMD)-based methods are presented to retrieve wind direction from rain-contaminated X-band nautical radar sea surface images. Each radar image is first decomposed into disparate intrinsic mode function (IMF) components using 1-D EEMD or 2-D EEMD. Then, the standard deviation of one IMF component or the combination of several IMF components as a function of azimuth is least-squares fitted to a harmonic function to determine the wind direction. Tests of the proposed algorithms are conducted by employing radar and anemometer data collected in a sea trial during rain events off the east coast of Canada. The results show that compared with the 1-D discrete-Fourier-transform-based method, both the 1-D- and 2-D-EEMD-based algorithms improve the wind direction results in rain events, showing a reduction of 7.4° and 8.7°, respectively, in the root-mean-square difference with respect to the reference.
Wind Direction Estimation From Rain-Contaminated Marine Radar Data Using the Ensemble Empirical Mode Decomposition Method
Two ensemble empirical mode decomposition (EEMD)-based methods are presented to retrieve wind direction from rain-contaminated X-band nautical radar sea surface images. Each radar image is first decomposed into disparate intrinsic mode function (IMF) components using 1-D EEMD or 2-D EEMD. Then, the standard deviation of one IMF component or the combination of several IMF components as a function of azimuth is least-squares fitted to a harmonic function to determine the wind direction. Tests of the proposed algorithms are conducted by employing radar and anemometer data collected in a sea trial during rain events off the east coast of Canada. The results show that compared with the 1-D discrete-Fourier-transform-based method, both the 1-D- and 2-D-EEMD-based algorithms improve the wind direction results in rain events, showing a reduction of 7.4° and 8.7°, respectively, in the root-mean-square difference with respect to the reference.
Wind Direction Estimation From Rain-Contaminated Marine Radar Data Using the Ensemble Empirical Mode Decomposition Method
Liu, Xinlong (Autor:in) / Huang, Weimin / Gill, Eric W
2017
Aufsatz (Zeitschrift)
Englisch
Lokalklassifikation TIB:
770/3710/5670
BKL:
38.03
Methoden und Techniken der Geowissenschaften
/
74.41
Luftaufnahmen, Photogrammetrie
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