Towards surface mapping using GNSS-IR
Published in IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2023
For more than three decades Global Navigation Satellite Systems (GNSS) were not only seen as a way to obtain a precise position but also as a way to extract geophysical information thanks to reflected signals from surfaces surrounding the receiver as in GNSS Reflectometry (GNSS-R). One of the main GNSS-R techniques, GNSS Interferometric Reflectometry (GNSS-IR), consists of collecting a direct signal and its reflection with a receiver close to the ground. Both signals coherently interfere at the antenna level which results in an interference pattern that can be interpreted in order to extract receiver height or soil moisture for instance. So far, the underlying assumptions for this technique were to consider a flat infinite and homogeneous reflecting surface which contradicts with the ability to map a surface that would need to be non-homogeneous. In this study, an improvement of the signal model is proposed to take into account variations of the reflection coefficient along the surface. This work is limited to a 1D configuration. Closed-form expressions are derived to invert the problem based on the EXtended Invariance Principle (EXIP). Finally, numerical results illustrate this approach.
Recommended citation: Corentin Lubeigt, François Vincent, "Towards surface mapping using GNSS-IR," IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Los Sueños, Costa Rica, December 2023.