In this paper, the synthetic aperture radar (SAR) azimuth cutoff method is thoroughly revised and a new and general implementation is proposed. The key roles of the pixel spacing, the size of the image box, and the texture of the SAR scene are analyzed and optimized in terms of azimuth cutoff (λc) estimation. The reliability of the λc estimation is analyzed by measuring the distance between the measured and fitted autocorrelation functions. This analysis shows that it is of paramount importance to filter unfeasible/unreliable λc values. To identify those values in an objective way, a criterion that is based on the χ2 test performed over a large data set of Sentinel-1 SAR imagery is defined and proven to be effective. The new robust implementation of the λc estimation at about 1-km grid spacing is then used to produce averaged λc at about 10-km grid spacing. The performance of the new estimation procedure, analyzed using a λc-to-wind-speed forward model, is shown to provide improved wind speed retrievals, with a root-mean-square error of 1.8-2 m/s when verified against independent numerical weather prediction model output and scatterometer winds.
A Novel Azimuth Cutoff Implementation to Retrieve Sea Surface Wind Speed From SAR Imagery
Grieco G.;
2019
Abstract
In this paper, the synthetic aperture radar (SAR) azimuth cutoff method is thoroughly revised and a new and general implementation is proposed. The key roles of the pixel spacing, the size of the image box, and the texture of the SAR scene are analyzed and optimized in terms of azimuth cutoff (λc) estimation. The reliability of the λc estimation is analyzed by measuring the distance between the measured and fitted autocorrelation functions. This analysis shows that it is of paramount importance to filter unfeasible/unreliable λc values. To identify those values in an objective way, a criterion that is based on the χ2 test performed over a large data set of Sentinel-1 SAR imagery is defined and proven to be effective. The new robust implementation of the λc estimation at about 1-km grid spacing is then used to produce averaged λc at about 10-km grid spacing. The performance of the new estimation procedure, analyzed using a λc-to-wind-speed forward model, is shown to provide improved wind speed retrievals, with a root-mean-square error of 1.8-2 m/s when verified against independent numerical weather prediction model output and scatterometer winds.File | Dimensione | Formato | |
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