In this book, research for improving sea surface remote sensing using the Global Navigation Satellite System-Reflectometry (GNSS-R) signals is presented. Firstly, a method to enable the simulation of GNSS-R delay Doppler Map (DDM) of an oil slicked sea surfaces under general scenarios is proposed. The DDM of oil slicked sea surface under general scenarios is generated by combining the mean-square slope model for oil slicked/clean surfaces and the GNSS-R Zavorotny-Voronovich (Z-V) scattering model. Secondly, a technique to detect sea surface oil spills using reflections from Global Navigation Satellite System (GNSS) satellites is presented. This technique is implemented by compensating the distortion induced during the DDM deconvolution process of scattering coefficient retrieval and employing the spatial integration approach (SIA) to retrieve the scattering coefficients unambiguously using the DDMs obtained by two separate antenna beams. Lastly, a novel method is presented to retrieve sea surface wind speed and direction by fitting the two-dimensional simulated GNSS-R DDMs to measured data.
"synopsis" may belong to another edition of this title.
Chen Li was born in Qingdao, Shandong, China. He received the M.Eng. degree in electrical engineering from Memorial University of Newfoundland (MUN), St. John’s, NL, Canada, in 2014. His research interests include sea surface oil spill detection and ocean wind field retrieval using GNSS-R.
"About this title" may belong to another edition of this title.
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, research for improving sea surface remote sensing using the Global Navigation Satellite System-Reflectometry (GNSS-R) signals is presented. Firstly, a method to enable the simulation of GNSS-R delay Doppler Map (DDM) of an oil slicked sea surfaces under general scenarios is proposed. The DDM of oil slicked sea surface under general scenarios is generated by combining the mean-square slope model for oil slicked/clean surfaces and the GNSS-R Zavorotny-Voronovich (Z-V) scattering model. Secondly, a technique to detect sea surface oil spills using reflections from Global Navigation Satellite System (GNSS) satellites is presented. This technique is implemented by compensating the distortion induced during the DDM deconvolution process of scattering coefficient retrieval and employing the spatial integration approach (SIA) to retrieve the scattering coefficients unambiguously using the DDMs obtained by two separate antenna beams. Lastly, a novel method is presented to retrieve sea surface wind speed and direction by fitting the two-dimensional simulated GNSS-R DDMs to measured data. 100 pp. Englisch. Seller Inventory # 9783659587870
Seller: moluna, Greven, Germany
Condition: New. Seller Inventory # 5166862
Quantity: Over 20 available
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book, research for improving sea surface remote sensing using the Global Navigation Satellite System-Reflectometry (GNSS-R) signals is presented. Firstly, a method to enable the simulation of GNSS-R delay Doppler Map (DDM) of an oil slicked sea surfaces under general scenarios is proposed. The DDM of oil slicked sea surface under general scenarios is generated by combining the mean-square slope model for oil slicked/clean surfaces and the GNSS-R Zavorotny-Voronovich (Z-V) scattering model. Secondly, a technique to detect sea surface oil spills using reflections from Global Navigation Satellite System (GNSS) satellites is presented. This technique is implemented by compensating the distortion induced during the DDM deconvolution process of scattering coefficient retrieval and employing the spatial integration approach (SIA) to retrieve the scattering coefficients unambiguously using the DDMs obtained by two separate antenna beams. Lastly, a novel method is presented to retrieve sea surface wind speed and direction by fitting the two-dimensional simulated GNSS-R DDMs to measured data.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 100 pp. Englisch. Seller Inventory # 9783659587870
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book, research for improving sea surface remote sensing using the Global Navigation Satellite System-Reflectometry (GNSS-R) signals is presented. Firstly, a method to enable the simulation of GNSS-R delay Doppler Map (DDM) of an oil slicked sea surfaces under general scenarios is proposed. The DDM of oil slicked sea surface under general scenarios is generated by combining the mean-square slope model for oil slicked/clean surfaces and the GNSS-R Zavorotny-Voronovich (Z-V) scattering model. Secondly, a technique to detect sea surface oil spills using reflections from Global Navigation Satellite System (GNSS) satellites is presented. This technique is implemented by compensating the distortion induced during the DDM deconvolution process of scattering coefficient retrieval and employing the spatial integration approach (SIA) to retrieve the scattering coefficients unambiguously using the DDMs obtained by two separate antenna beams. Lastly, a novel method is presented to retrieve sea surface wind speed and direction by fitting the two-dimensional simulated GNSS-R DDMs to measured data. Seller Inventory # 9783659587870
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Sea Surface Remote Sensing Using GNSS-Reflectometry | Oil Spill Detection And Wind Field Retrieval | Chen Li (u. a.) | Taschenbuch | 100 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659587870 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 105100365
Seller: Mispah books, Redhill, SURRE, United Kingdom
paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book. Seller Inventory # ERICA82936595878776