Abstract
This work addresses the accuracy of the Global Navigation Satellite Systems (GNSS)-Reflectometry (GNSS-R) scatterometric measurements considering the presence of both coherent and incoherent scattered components, for both conventional GNSS-R (cGNSS-R) and interferometric GNSS-R (iGNSS-R) techniques. The coherent component is present for some type of surfaces, and it has been neglected until now because it vanishes for the sea surface scattering case. Taking into account the presence of both scattering components, the estimated Signal-to-Noise Ratio (SNR) for both techniques is computed based on the detectability criterion, as it is done in conventional GNSS applications. The non-coherent averaging operation is considered from a general point of view, taking into account that thermal noise contributions can be reduced by an extra factor of 0.88 dB when using partially overlapped or partially correlated samples. After the SNRs are derived, the received waveform’s peak variability is computed, which determines the system’s capability to measure geophysical parameters. This theoretical derivations are applied to the United Kingdom (UK) TechDemoSat-1 (UK TDS-1) and to the future GNSS REflectometry, Radio Occultation and Scatterometry on board the International Space Station (ISS) (GEROS-ISS) scenarios, in order to estimate the expected scatterometric performance of both missions.
Highlights
The analysis of the Signal-to-Noise Ratio (SNR) is very important to determine the variance of the radar cross section or reflectivity, and to assess the system’s capability and accuracy to measure geophysical parameters
Due to the low-power and high-phase noise of the Global Navigation Satellite Systems (GNSS) reflected signals both conventional GNSS-R (cGNSS-R) and interferometric GNSS-R (iGNSS-R) approaches tend to use ∼1 ms of coherent integration time and apply the non-coherent summations/averaging, which means that they work with the power waveforms instead of the complex-value voltage waveforms
If SNRd 1, SNRTHi → SNRTHc, and di0 → d0c. There is another aspect that is related to the definition of the detectability criterion, which is that the mean noise level value in the iGNSS-R case is not subtracted at the correlation peak by using the one computed at lags away from the correlation
Summary
The analysis of the SNR is very important to determine the variance of the radar cross section or reflectivity, and to assess the system’s capability and accuracy to measure geophysical parameters. In 2011, the scatterometric accuracy of a PARIS-like instrument using the iGNSS-R approach was presented [9] In all those studies, a Gaussian model like the one in [1] was assumed, because experimental evidence had confirmed that the sea-surface scattered signals follow complex. Map (DDM)s show a “K-shape” feature, as shown in [11], which indicates a presence of the coherent component, requiring the use of a Hoyt distribution to describe the statistics of the scattered signals Following this evidence, this work extends the scatterometric analysis performed in [9] to the cGNSS-R case, and includes the presence of the coherent component in the scattered signals that was not considered in previous works. This paper ends with a discussion and a concluding section highlighting the main achievements
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