An Empirical Mode Decomposition Method for Sea Surface Wind Measurements From X-Band Nautical Radar Data

作者：Huang Weimin^*; Liu Xinlong; Gill Eric W

来源：IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(11): 6218-6227.

DOI：10.1109/TGRS.2017.2723431

• Ensemble empirical mode decomposition (EEMD)
• rain
• wind
• X-band nautical radar

In this paper, sea surface wind direction and speed are obtained from X-band nautical radar images. A data control strategy is proposed to distinguish rain-free and rain-contaminated radar data. The radar data are decomposed by an ensemble empirical mode decomposition method into several intrinsic mode functions (IMFs) and a residual. A normalization scheme is applied to the first IMF to obtain the amplitude modulation (AM) component. Wind direction is determined from the residual for the rain-free and high-wind-speed rain-contaminated data, and from the AM portion of the first IMF for the low-wind-speed rain-contaminated data, based on curve fitting a harmonic function. Wind speed is determined from a combination of the residual and the AM part of the first IMF for both rain-free and rain-contaminated data using a logarithmic relationship. Results employing ship-borne radar and anemometer data collected in a sea trial off the east coast of Canada are presented. The root-mean-square differences for wind direction and speed measurements are 11.5 degrees and 1.31 m/s, respectively, compared with reference values from anemometers.

• 出版日期2017-11