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Analysis of C-band spaceborne scatterometers thermal noise
Elyouncha, A.; Neyt, X. (2014). Analysis of C-band spaceborne scatterometers thermal noise, in: Bostater, C.R. et al. (Ed.) Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2014. Proceedings of SPIE, the International Society for Optical Engineering, 9240: pp. 924006. https://dx.doi.org/10.1117/12.2068172
In: Bostater, C.R. et al. (Ed.) (2014). Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2014. Proceedings of SPIE, the International Society for Optical Engineering, 9240. SPIE: Amsterdam. , meer
In: Proceedings of SPIE, the International Society for Optical Engineering. SPIE: Bellingham, WA. ISSN 0277-786X; e-ISSN 1996-756X, meer
Peer reviewed article  

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Abstract
    A scatterometer is a radar designed to measure the backscattering coefficient of distributed targets. In order to compute the backscatter from the received power, the scatterometer measures also the thermal noise power. This noise signal is composed of two components, the receiver thermal noise and the viewed ground radiance. The first component is instrument dependent and hence independent of the target and viewing geometry. The second component is target and viewing geometry dependent, it is proportional to the ground target brightness temperature. In this paper the noise signal measured by C-band scatterometers on-board ERS-2 and Metop-A satellites is analyzed. It was found that the noise signal carries valuable geophysical information, which is worth to be exploited. It is shown that the noise signal varies spatially, temporally and with viewing geometry. Thus, different targets (ocean, sea ice, land) could be easily identified. A comparison was carried out between the scatterometer noise and AMSR-E radiometer brightness temperature and high correlation was found. The noise signal processing (mainly noise subtraction) is discussed, including the assessment of the Noise Equivalent Sigma Zero and the Signal-to-noise ratio. This analysis leads to a better understanding of the noise signal and its impact on the backscatter processing.

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