scholarly journals A Comparison between Drifter and X-Band Wave Radar for Sea Surface Current Estimation

2016 ◽  
Vol 8 (9) ◽  
pp. 695 ◽  
Author(s):  
Giovanni Ludeno ◽  
Carmelo Nasello ◽  
Francesco Raffa ◽  
Giuseppe Ciraolo ◽  
Francesco Soldovieri ◽  
...  
Keyword(s):  
Surface Current ◽  
Sea Surface ◽  
Current Estimation ◽  
X Band ◽  
Wave Radar

scholarly journals X-Band Wave Radar for Coastal Upwelling Detection off the Southern Coast of Sicily

2017 ◽  
Vol 34 (1) ◽  
pp. 21-31 ◽  
Author(s):  
F. Raffa ◽  
G. Ludeno ◽  
B. Patti ◽  
F. Soldovieri ◽  
S. Mazzola ◽  
...  
Keyword(s):  
Coastal Upwelling ◽  
Surface Current ◽  
Radar Data ◽  
Sea Surface ◽  
Open Sea ◽  
Independent Information ◽  
X Band ◽  
Wave Radar ◽  
Radar Data Processing

AbstractThe main aim of this work is to show the potentialities of an X-band radar system about the detection of the coastal upwelling phenomenon. This is made possible by means of the estimation of the sea surface current, which moves from the coastal areas toward the open sea for wind-induced upwelling events. The study presents the results of the X-band radar data processing for a system installed at Capo Granitola (southwestern Sicily). In particular, the radar data acquired in three different periods—namely, 5–6 November 2013, 8–9 February 2015, and 6 March 2015—indicated upwelling events. The occurrence of these events was confirmed by independent information derived from in situ wind data provided by a meteorological station and the analysis of the satellite-derived sea surface temperature (SST) and chlorophyll-a (Chl-a) concentration.

A hybrid method for surface current estimation using X-band nautical radar

2015 ◽  
Author(s):  
Al-Abbass Al-Habashneh ◽  
Cecilia Moloney ◽  
Eric W. Gill ◽  
Weimin Huang
Keyword(s):  
Hybrid Method ◽  
Surface Current ◽  
Current Estimation ◽  
X Band

Application of ESPRIT in broad beam HF ground wave radar sea surface current mapping

2004 ◽  
Vol 9 (2) ◽  
pp. 209-214 ◽  
Author(s):  
Liu Dan-hong ◽  
Wu Xiong-bin ◽  
Wen Bi-yang ◽  
Cheng Feng
Keyword(s):  
Surface Current ◽  
Sea Surface ◽  
Hf Ground Wave Radar ◽  
Broad Beam ◽  
Wave Radar ◽  
Ground Wave

scholarly journals Sea Surface Current Estimation Using Airborne Circular Scanning SAR with a Medium Grazing Angle

2018 ◽  
Vol 10 (2) ◽  
pp. 178
Author(s):  
Xueli Pan ◽  
Guisheng Liao ◽  
Zhiwei Yang ◽  
Hongxing Dang
Keyword(s):  
Grazing Angle ◽  
Surface Current ◽  
Sea Surface ◽  
Current Estimation

REMOCEAN: A Flexible X-Band Radar System for Sea-State Monitoring and Surface Current Estimation

2012 ◽  
Vol 9 (5) ◽  
pp. 822-826 ◽  
Author(s):  
F. Serafino ◽  
C. Lugni ◽  
G. Ludeno ◽  
D. Arturi ◽  
M. Uttieri ◽  
...  
Keyword(s):  
Surface Current ◽  
Radar System ◽  
State Monitoring ◽  
Sea State ◽  
Current Estimation ◽  
X Band

scholarly journals Gap Filling of the CALYPSO HF Radar Sea Surface Current Data through Past Measurements and Satellite Wind Observations

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Adam Gauci ◽  
Aldo Drago ◽  
John Abela
Keyword(s):  
Oil Spills ◽  
Surface Current ◽  
Radar Data ◽  
Current Data ◽  
Hf Radar ◽  
Sea Surface ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Spatial Coverage ◽  
Essential Components

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.

Low Wave Number Radar Image Energy Influence on Determining Current

2012 ◽  
Vol 433-440 ◽  
pp. 6054-6059
Author(s):  
Gan Nan Yuan ◽  
Rui Cai Jia ◽  
Yun Tao Dai ◽  
Ying Li
Keyword(s):  
Wave Spectrum ◽  
Surface Current ◽  
Sea Surface ◽  
Radar Image ◽  
Wave Number ◽  
Sea State ◽  
Low Frequencies ◽  
In Situ Data ◽  
Main Effects

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.

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