A New Algorithm for Retrieving Sea Surface Current Direction from Sar Doppler Information

Author(s):  
Xiaobo Yang ◽  
Yijun He
2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Adam Gauci ◽  
Aldo Drago ◽  
John Abela

High frequency (HF) radar installations are becoming essential components of operational real-time marine monitoring systems. The underlying technology is being further enhanced to fully exploit the potential of mapping sea surface currents and wave fields over wide areas with high spatial and temporal resolution, even in adverse meteo-marine conditions. Data applications are opening to many different sectors, reaching out beyond research and monitoring, targeting downstream services in support to key national and regional stakeholders. In the CALYPSO project, the HF radar system composed of CODAR SeaSonde stations installed in the Malta Channel is specifically serving to assist in the response against marine oil spills and to support search and rescue at sea. One key drawback concerns the sporadic inconsistency in the spatial coverage of radar data which is dictated by the sea state as well as by interference from unknown sources that may be competing with transmissions in the same frequency band. This work investigates the use of Machine Learning techniques to fill in missing data in a high resolution grid. Past radar data and wind vectors obtained from satellites are used to predict missing information and provide a more consistent dataset.


2012 ◽  
Vol 433-440 ◽  
pp. 6054-6059
Author(s):  
Gan Nan Yuan ◽  
Rui Cai Jia ◽  
Yun Tao Dai ◽  
Ying Li

In the radar imaging mechanism different phenomena are present, as a result the radar image is not a direct representation of the sea state. In analyzing radar image spectra, it can be realized that all of these phenomena produce distortions in the wave spectrum. The main effects are more energy for very low frequencies. This work investigates the structure of the sea clutter spectrum, and analysis the low wave number energy influence on determining sea surface current. Then the radar measure current is validated by experiments. By comparing with the in situ data, we know that the radar results reversed by image spectrum without low wave number spectrum have high precision. The low wave number energy influent determining current seriously.


2021 ◽  
Author(s):  
Anis Elyouncha ◽  
Leif E. B. Eriksson

<p><span>Synthetic aperture radar (SAR) has become an essential component in ocean remote sensing due it’s </span><span>high</span> <span>sensitivity</span><span> to sea surface dynamics and its high spatial resolution. </span><span>The ALOS-</span><span>2 SAR</span><span> data are </span> underutilized <span>for</span><span> ocean surface wind and current retrieval. Althou</span><span>g</span><span>h the primary goals of the </span><span>ALOS-2</span><span> mission are focused on land applications, the extension of the satellite scenes over the coast</span><span>al areas</span><span> offers an opportunity for ocean applications. Th</span><span>e</span><span> underutilization </span><span>of ALOS-2 data </span><span>is mainly due to the fact that at low radar frequencies, e.g. L-band, the sensitivity of the radar scattering coefficient to wind speed and the sensitivity of the Doppler frequency shift to sea surface velocity is lower than at higher frequencies, e.g. C- </span><span>and</span><span> X-</span><span>band</span><span>. </span><span>This is also due to the fact that most of ALOS-2 images are acquired in HH or HV polarization while the VV polarization is often preferred in ocean applications due the higher signal to noise ratio. </span></p><p>The wind speed is retrieved from Sentinel-1 and ALOS-2 using the existing empirical C- and L-band geophysical model functions. For Sentinel-1, the Doppler frequency shift provided in the OCN product is used. For ALOS-2, the Doppler frequency shift is estimated from the single look complex data using the pulse-pair processing method. The estimated Doppler shift converted to the surface radial velocity and the velocity is calibrated using land as a reference. The estimated L-band Doppler shift and surface velocity is compared to the C-band Doppler shift provided in the Sentinel-1 OCN product. Due the difference in the local time of ascending node (about 6 hours at the equator) of the two satellites, a direct pixel-by-pixel comparison is not possible, i.e. the wind and surface current can not be assumed to be constant during such a large time difference. Thus, the retrieved wind from each sensor is compared separately to model data and in-situ observations.</p><p>In this paper, the quality of the wind speed retrieved from the L-band SAR (ALOS-2) in coastal areas is assessed and compared to the C-band SAR (Sentinel-1). In addition, the feasibility of the surface current retrieval from the L-band Doppler frequency shift is investigated and also compared to Sentinel-1. Examples will be shown and discussed. This opens an opportunity for synergy between L-band and C-band SAR missions to increase the spatial and temporal coverage, which is one of the main limitations of SAR application in ocean remote sensing.</p>


2019 ◽  
Vol 11 (11) ◽  
pp. 1264 ◽  
Author(s):  
Zhimin Ma ◽  
Guoqi Han

Utilizing a high-resolution (2-km) coastal ocean model output off Eastern Newfoundland, this paper explores the potential for reconstructing the sea surface height (SSH) and the surface inshore Labrador Current from high-resolution SSH data of the upcoming Surface Water and Ocean Topography (SWOT) satellite mission. The model results are evaluated against in-situ data from tide gauges and nadir altimetry for the period from June to October, 2010. The hourly model SSH output is used as true SSH and sampled along-swath with expected measurement errors by using a SWOT simulator, which produces SWOT-like data. We reconstruct half-day SSH fields from the SWOT-like data using optimal interpolation and average them into weekly fields. The average normalized root-mean-square difference between the weekly reconstructed SSH field and the model SSH filed is 0.07 for the inshore Labrador Current. Between the geostrophic surface current derived from the reconstructed SSH field and the model surface current, the average normalized root-mean-square difference is 0.26 for the inshore Labrador Current. For the surface unit-depth transport of the inshore Labrador Current, the normalized root-mean-square differences are 0.32–0.38 between the reconstructed current and the model current.


2020 ◽  
Vol 177 (12) ◽  
pp. 5969-5992
Author(s):  
Siva Srinivas Kolukula ◽  
Balaji Baduru ◽  
P. L. N. Murty ◽  
J. Pavan Kumar ◽  
E. Pattabhi Rama Rao ◽  
...  

2004 ◽  
Vol 9 (2) ◽  
pp. 209-214 ◽  
Author(s):  
Liu Dan-hong ◽  
Wu Xiong-bin ◽  
Wen Bi-yang ◽  
Cheng Feng

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