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Journal Articles IEEE Transactions on Geoscience and Remote Sensing Year : 2022

Speckle noise spectrum at near-nadir incidence angles for a time-varying sea surface


Speckle noise is inherent to radar measurements. For applications which need both a high temporal and high spatial resolution, a classical method for the reduction of the speckle noise by filtering the backscattered signal may not be sufficient. In particular, when radar observations are used to estimate ocean wave spectra from relative fluctuations of the radar signal within a given footprint, a method must be implemented to correct for the speckle effect in the Fourier domain (i.e. density spectrum). A theoretical background to model the speckle density spectrum for a radar with near-nadir incidences was proposed by Jackson in 1981 but it is based on a stationary sea surface assumption and ignores the variation of the main factor in the four-frequency moment near the origin. In this paper, we revisit this theoretical background to extend this model to a time-varying sea surface and alleviate some assumptions on the Fresnel phase formulation. The results from the model applied in the configuration of an airborne system indicate that not only the displacement of the radar but also the dynamic properties of the sea surfaces have a significant effect on the speckle noise spectrum in certain directions of observations. The effects depend on the radar look direction in azimuth, and on sea surface conditions (wind speed, wind direction with respect to the aircraft route, surface wave spectrum). This new model is validated against observations of the airborne near-nadir incidence scatterometer –KuROS. We show in particular that the errors between the experimental estimation of the omni-directional speckle noise spectrum from KuROS and the prediction by our model are below 10%.
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insu-03008365 , version 1 (16-11-2020)



Ping Chen, Danièle Hauser, Shihao Zou, Jianyang Si, Eva Le Merle. Speckle noise spectrum at near-nadir incidence angles for a time-varying sea surface. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60, pp.4200320. ⟨10.1109/TGRS.2020.3037910⟩. ⟨insu-03008365⟩
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