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A parametric inversion scheme for the SAR retrieval of 2-D ocean wave spectra

Schulz-Stellenfleth, Johannes and Lehner, Susanne (2006) A parametric inversion scheme for the SAR retrieval of 2-D ocean wave spectra. In: Proceedings of SEASAR 2006 (SP-613), pp. 1-6. SEASAR 2006, 2006-01-23 - 2006-01-26, Frascati (Italy).

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A parametric inversion scheme for the retrieval of two-dimensional ocean wave spectra from look cross spectra (SLCS) acquired by spaceborne synthetic aperture radar (SAR) is presented. The scheme uses prior information from numerical wave models to deal with the information loss caused by the nonlinear SAR ocean wave imaging mechanism. The Partition Rescaling and Shift Algorithm (PARSA) is based on a maximum a posteriori approach in which an optimal estimate of a wave spectrum for a given measured SLCS and additional prior knowledge is calculated. The method is based on explicit models for measurement errors, as well as uncertainties in the SAR imaging model and the model wave spectra used as prior information. The correction parameters for the SAR imaging model are estimated as part of the retrieval process. The rigorous stochastic approach enables the estimation of the error covariance matrix of the retrieved parameters. Uncertainties in the prior wave spectrum are expressed in terms of transformation variables, which are defined for each wave system in the spectrum, describing rotations, rescaling of wavenumbers and energy, as well as changes of directional spreading. A new partitioning method is used which allows overlapping partitions and thus avoids discontinuities occurring in algorithms used so far. The PARSA wave spectra retrieval is equivalent to a minimization problem with regard to the transformation variables and parameters of the imaging model. A Levenberg Marquard method is used to find a numerical solution. The inversion is performed on a polar grid with a dimension, which is an order of magnitude smaller than the typical cartesian grids used so far. The reduced dimension enables the use of an extended quasi-linear approximation of the imaging model with non-diagonal Jacobian matrix, leading to a high stability of the algorithm. The scheme is tested using both ERS-2 SAR and ENVISAT ASAR data. It is shown that the method is able to extract information from cross spectra even if there are strong errors in the SAR imaging model. It is demonstrated that the algorithm makes use of the new phase information contained in cross spectra, which is of particular importance for multi-modal sea states. Global statistics are presented for a global data set of reprocessed ERS-2 SAR wave mode SLCS acquired in southern winter 1996. Comparisons with NDBC buoy data are presented. The statistical analysis includes standard wave parameters like the significant wave height as well as parameters which are relevant for the investigation of extreme wave conditions like,e.g., the Benjamin Feir Index.

Item URL in elib:https://elib.dlr.de/43679/
Document Type:Conference or Workshop Item (Speech)
Title:A parametric inversion scheme for the SAR retrieval of 2-D ocean wave spectra
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Date:January 2006
Journal or Publication Title:Proceedings of SEASAR 2006
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 1-6
EditorsEmailEditor's ORCID iDORCID Put Code
Keywords:SAR, 2-D Ocean Wave Spectra
Event Title:SEASAR 2006
Event Location:Frascati (Italy)
Event Type:international Conference
Event Start Date:23 January 2006
Event End Date:26 January 2006
HGF - Research field:Aeronautics, Space and Transport (old)
HGF - Program:Space (old)
HGF - Program Themes:W EO - Erdbeobachtung
DLR - Research area:Space
DLR - Program:W EO - Erdbeobachtung
DLR - Research theme (Project):W - Vorhaben Entwicklung und Erprobung von Verfahren zur Gewässerfernerkundung (old)
Location: Berlin-Adlershof , Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Marine Remote Sensing
Deposited On:26 Jun 2007
Last Modified:24 Apr 2024 19:05

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