On the delay and Gaussian random scattering estimation for GNSS-R applications
Published in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2026
The delay-Doppler map is the primary observable used in most Global Navigation Satellite System (GNSS) reflectometry retrieval algorithms. The standard underlying assumption is to consider a conditional (deterministic) signal model, whereby all unknown parameters are assumed to be deterministic. However, a Gaussian random surface scattering model, leading to an unconditional (stochastic) signal model (USM), may be more informative. To assess the potential benefits of the USM, we first consider delay and Gaussian source mean and variance estimation. For these, we derive compact, closedform, unconditional Cram´er–Rao bound (CRB) expressions and the corresponding maximum likelihood estimators. The results are validated with a representative GNSS signal.
Recommended citation: Filippo Torrisi, Corentin Lubeigt, Jordi Vilà-Valls, Eric Chaumette, "On the delay and Gaussian random scattering estimation for GNSS-R applications," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Washington, D.C., USA, August 2026.