Abstract
Low-frequency space-based synthetic aperture radar (SAR) is an ideal sensor for measuring forest biomass, but can suffer from ionospheric effects. The variation in total electron content (TEC), originating from ionospheric turbulence, causes the along track point spread function (PSF) to degrade in a manner which depends on ionospheric conditions. In this study, the effect of this PSF on the single point statistics (probability density function) and two point statistics (autocorrelation function (ACF)) is derived. It is shown that the K -distribution order parameter is directly proportional to the ionospheric turbulence, as quantified by C k L . The complex ACF is a measure of amplitude scintillation, and the intensity ACF is a measure of both the order parameter and the terrain correlation length. A simulation is performed which clearly shows that measuring the order parameter ratio between ionospherically disturbed and undisturbed images is a measure of C k L . This measure can be used two orders of magnitude below the point where the ionosphere causes defocusing of the SAR image. It is concluded that the usefulness of this new measure can only be verified by experimental data since the temporal stability of the underlying order parameter is unknown.
Highlights
1.1 BackgroundSpace-based synthetic aperture radar (SAR) is a useful remote sensing tool, being relatively unaffected by tropospheric weather
The simulation clearly demonstrates that it is possible to measure the effects of ionospheric scintillation on the clutter order parameter two orders of magnitude below the point where image defocusing occurs
The same image was used to measure the order parameter, but in practice a different realisation of the real clutter will occur on each satellite imaging pass
Summary
Space-based synthetic aperture radar (SAR) is a useful remote sensing tool, being relatively unaffected by tropospheric weather. A promising application for space-borne SAR is the measurement of the Earth’s forest biomass, an important parameter for accurate prediction of global climate change This requires a low-frequency SAR (1 GHz and below) with foliage penetration characteristics that result in a backscatter that depends on the volumetric vegetation. The main effect of the ionosphere is to perturb the phase of an RF signal, the size of the effect being determined by both the RF frequency and by the total electron content (TEC) experienced by a signal passing through it This phase perturbation manifests itself in a variety of ways in the SAR image, resulting in Faraday rotation, a time delay that causes image shift, and defocusing in both the range and azimuth directions.
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