A global dataset of complex synthetic aperture (SAR) images is processed from wave mode raw data acquired by the ERS-2 satellite. Using these data, different algorithms for wind and wave measurements recently developed in view of future ENVISAT ASAR data are analyzed on a statistical basis. Different aspects of complex SAR wave mode processing with the DLR processor BSAR are discussed and global statistics of processing parameters are presented. Single-look complex (SLC) imagettes give the opportunity to apply multilook techniques in range as well as in azimuth. Such methods are used to reduce speckle noise or to analyze the time evolution of the ocean surface cross section during SAR integration time. A global analysis of different new algorithms for wind and ocean wave measurements, taking advantage of SLC data, is given. Wind speed is estimated with the azimuthal cross-correlation algorithm (CCA). As a modification of the existing CCA, range multilooking is used to deal with the speckle bias. Homogeneity of the imagettes is considered. Wind speed is derived from mean SAR image intensities taking into account wind direction (CMOD algorithm). Comparison with collocated ERS-2 scatterometer data shows reasonable agreement with the CCA and good agreement for the CMOD approach. Using imagettes instead of image power spectra allows the authors to study ocean surface features caused by natural slicks, sea ice, or atmospheric processes. The impact of these phenomena on SCAT measurements is considered. Cross spectral methods are used to derive the ocean wave propagation direction from complex imagettes on a global basis. Comparison with model data provided by the European Center for Medium Range Weather Forecast (ECMWF) shows good agreement.
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Lehner et al. (2000) studied this question.
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