One important parameter in reconstructing and predicting the sea surface elevation from radar images is the surface current. The common method to derive the current is based on 3DFFT with which the (absolute) frequency is derived from a series of images and is fitted to the encounter dispersion relation that consist of the intrinsic exact dispersion relation for linear waves with an additional term that contains the current velocity to be found. The derived dispersion relation will be inaccurate because the images contain many inaccuracies from noise, shadowing, and other radar effects. This paper proposes an alternative method to determine the surface current. Following the method of the Dynamic Averaging and Evolution Scenario (DAES) as presented in [1], the idea is to choose the current velocity that minimizes the difference between an image at a previous time that has been evolved to the time of another image. In order to reduce inaccuracies, an averaging procedure over various images is applied. The method is tested on synthetic data to quantify the accuracy of the results. The robustness of the method will be investigated for several cases of different current parameters (speed and direction) for ensembles of seas with different peak frequency of characteristic sea states.
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ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering
June 25–30, 2017
Trondheim, Norway
Conference Sponsors:
- Ocean, Offshore and Arctic Engineering Division
ISBN:
978-0-7918-5774-8
PROCEEDINGS PAPER
Dynamic Averaging Method to Detect Sea Surface Current From Radar Images
Andreas P. Wijaya
Andreas P. Wijaya
LabMath-Indonesia, Bandung, Indonesia
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Andreas P. Wijaya
LabMath-Indonesia, Bandung, Indonesia
Paper No:
OMAE2017-62396, V07BT06A035; 5 pages
Published Online:
September 25, 2017
Citation
Wijaya, AP. "Dynamic Averaging Method to Detect Sea Surface Current From Radar Images." Proceedings of the ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering. Volume 7B: Ocean Engineering. Trondheim, Norway. June 25–30, 2017. V07BT06A035. ASME. https://doi.org/10.1115/OMAE2017-62396
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