Abstract
It is well known that reflected signals from Global Navigation Satellite Systems (GNSS) can be used for altimetry applications, such as monitoring of water levels and determining snow height. Due to the interference of these reflected signals and the motion of satellites in space, the signal-to-noise ratio (SNR) measured at the receiver slowly oscillates. The oscillation rate is proportional to the change in the propagation path difference between the direct and reflected signals, which depends on the satellite elevation angle. Assuming a known receiver position, it is possible to compute the distance between the antenna and the surface of reflection from the measured oscillation rate. This technique is usually known as the interference pattern technique (IPT). In this paper, we propose to normalize the measurements in order to derive an alternative model of the SNR variations. From this model, we define a maximum likelihood estimate of the antenna height that reduces the estimation time to a fraction of one period of the SNR variation. We also derive the Cramér–Rao lower bound for the IPT and use it to assess the sensitivity of different parameters to the estimation of the antenna height. Finally, we propose an experimental framework, and we use it to assess our approach with real GPS L1 C/A signals.
Highlights
Global Navigation Satellite Systems reflectometry (GNSS-R) is a well-established method for remotely sensing many relevant geophysical properties of the reflection surfaces
To reduce the estimation time to a fraction of one period of the signal-to-noise ratio (SNR) variations, we propose an alternative model for the measured SNR
We used an interference pattern technique (IPT) to estimate the height between an antenna and a ground surface, where a GNSS signal has been reflected
Summary
Global Navigation Satellite Systems reflectometry (GNSS-R) is a well-established method for remotely sensing many relevant geophysical properties of the reflection surfaces. Assuming that the antenna position is known, we can compute the position of the surface of reflection This approach provides precise localization and dating of the measures that allows for spatio-temporal comparison of water levels and snow cover, respectively [5,6,7,8]. This normalized model is based on the normalization of the measured signal amplitudes and is possible only after an initial calibration step This calibration step consists of varying the antenna height of the receiver a value dh in order to obtain the minimum and maximum value of SNR for a given satellite elevation.
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