Abstract
Soil moisture is an important factor affecting the global climate and environment, which can be monitored by microwave remote sensing all day and under all weather conditions. However, existing monostatic radars and microwave radiometers have their own limitations in monitoring soil moisture with shallower depths. The emerging remote sensing of signal of opportunity (SoOp) provides a new method for soil moisture monitoring, but only an experimental perspective was proposed at present, and its mechanism is not clear. In this paper, based on the traditional surface scattering models, we employed the polarization synthesis method, the coordinate transformation, and the Mueller matrix, to develop bistatic radar circular polarization models that are suitable for SoOP remote sensing. Using these models as a tool, the bistatic scattering versus the observation frequency, soil moisture, scattering zenith angle, and scattering azimuth at five different circular polarizations (LR, HR, VR, + 45° R, and −45° R) are simulated and analyzed. The results show that the developed models can determine the optimal observation combination of polarizations and observation angle. The systematic analysis of the scattering characteristics of random rough surfaces provides an important guiding significance for the design of space-borne payloads, the analysis of experimental data, and the development of backward inversion algorithms for more effective SoOP remote sensing.
Highlights
Soil moisture is an important factor affecting the global climate and environment
The random rough surface scattering model provides a mechanism for the sensitivity analysis of surface parameters in signal of opportunity (SoOP) remote sensing
In the past two decades, we witnessed the promising development of GNSS-R remote sensing
Summary
Soil moisture is an important factor affecting the global climate and environment. Its existence in the earth system and its spatial transmission mode play a vital role in the global energy balance. Traditional observation methods mainly use observations at discrete stations or corresponding meteorological stations, which can only represent a limited observation area (≈10–100 cm) They are time-consuming and labor-intensive and cannot meet the needs of large-scale and high-efficiency soil moisture observation. The unique observation geometry model of the bistatic radar has become a new method and technology for remote sensing monitoring of soil moisture and vegetation. The emerging signal of opportunity (SoOP) technology uses the existing navigation satellite group or communication satellites as the signal transmission sources, and only needs to develop a special reflected signal receiver to achieve effective monitoring of soil moisture in bistatic radar mode [4,5,6]. For SoOP soil moisture remote sensing, it is important to fully excavate the polarization characteristic information of navigation satellite signals.
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