A. Alonso-Arroyo

Retrieval of Significant Wave Height and Mean Sea Surface Level Using the GNSS-R Interference Pattern Technique: Results From a Three-Month Field Campaign

Since 1993, when the European Space Agency (ESA) proposed the use of Global Navigation Satellite Systems reflected signals for sea mesoscale altimetry, a wide range of applications have appeared. This paper focuses on the retrieval of significant wave height (SWH) and the mean sea surface level (MSSL) from a ground-based experiment using the interference pattern technique (IPT). Two different observables on the IPT are analyzed: the oscillation frequency and the angle where coherency is lost. The point where coherency in the reflection process is lost can be related to the Rayleigh criterion for smooth surfaces and helps to determine the SWH. Spectral analysis on the interference pattern helps to determine the MSSL. A three-month field campaign was performed on the “Pont del Petroli” pier, Badalona, Spain, to see how the reflected GNSS signals were affected by coastal sea state and check previous assumptions. Results from this field experiment are shown, confirming that the SWH can be retrieved with accuracy of 6 cm and the MSSL with 4 cm. Estimations of both parameters are obtained every 30 min approximately.

Improving the Accuracy of Soil Moisture Retrievals Using the Phase Difference of the Dual-Polarization GNSS-R Interference Patterns

Soil moisture (SM) is a key parameter in the climate studies at a global scale and a very important parameter in applications such as precision agriculture at a local scale. The Global Navigation Satellite Systems Interference Pattern Technique (IPT) has proven to be a useful technique for the determination of SM, based on observations at vertical polarization (V-Pol) due to the Brewster angle. The IPT can be applied at both V-Pol and horizontal polarization (H-Pol) at the same time, observing the Brewster angle only at V-Pol. This letter presents a measurement technique based on tracking the phase difference between V-Pol and H-Pol interference patterns to improve the accuracy of the Brewster angle determination and, consequently, that of the SM retrievals. This technique benefits from the different phase behavior of the reflection coefficients between H-Pol and V-Pol in the angular observation range. To be sensitive to the phase difference, the Rayleigh criterion for smooth surfaces must be accomplished. This technique is not sensitive to topography as it is intrinsically corrected. Experimental results are presented to validate the proposed algorithm.

On the synergy of airborne GNSS-R and landsat 8 for soil moisture estimation

While the synergy between thermal, optical, and passive microwave observations is well known for the estimation of soil moisture and vegetation parameters, the use of remote sensing sources based on the Global Navigation Satellite Systems (GNSS) remains unexplored. During an airborne campaign performed in August 2014, over an agricultural area in the Duero basin (Spain), an innovative sensor developed by the Universitat Politecnica de Catalunya-Barcelona Tech based on GNSS Reflectometry (GNSS-R) was tested for soil moisture estimation. The objective was to evaluate the combined use of GNSS-R observations with a time-collocated Landsat 8 image for soil moisture retrieval under semi-arid climate conditions. As a ground reference dataset, an intensive field campaign was carried out. The Light Airborne Reflectometer for GNSS-R Observations (LARGO) observations, together with optical, infrared, and thermal bands from Landsat 8, were linked through a semi-empirical model to field soil moisture. Different combinations of vegetation and water indices with LARGO subsets were tested and compared to the in situ measurements. Results showed that the joint use of GNSS-R reflectivity, water/vegetation indices and thermal maps from Landsat 8 not only allows capturing soil moisture spatial gradients under very dry soil conditions, but also holds great promise for accurate soil moisture estimation (correlation coefficients greater than 0.5 were obtained from comparison with in situ data).

Analysis of Spaceborne GNSS-R Delay-Doppler Tracking

For spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R), the delay and Doppler frequency conditions dynamically change, so the compensation of the delay and Doppler errors using tracking is important to the altimetric and scatterometric performances. This work presents the characteristics of the delay and the Doppler frequency in spaceborne GNSS-R, such as the range of them, the Doppler spreading width, and the change rate. They are important considerations for design of the delay and Doppler tracking strategy. The characteristics of delay-Doppler conditions of spaceborne GNSS-R are presented with additional considerations for tracking design. The tracking methods are discussed, and the error impacts are visually demonstrated by using the spaceborne measured data from United Kingdoms Disaster Monitoring Constellation (UK-DMC) satellite.

SNR Degradation in GNSS-R Measurements Under the Effects of Radio-Frequency Interference

Radio-frequency interference (RFI) is a serious threat for systems working with low power signals such as those coming from the global navigation satellite systems (GNSS). The spectral separation coefficient (SSC) is the standard figure of merit to evaluate the signal-to-noise ratio (SNR) degradation due to the RFI. However, an in-depth assessment in the field of GNSS-Reflectometry (GNSS-R) has not been performed yet, and particularly, about which is the influence of the RFI on the so-called delay-Doppler map (DDM). This paper develops a model that evaluates the contribution of intra-/inter-GNSS and external RFI effects to the degradation of the SNR in the DDM for both conventional and interferometric GNSS-R techniques. Moreover, a generalized SSC is defined to account for the effects of nonstationary RFI signals. The results show that highly directive antennas are necessary to avoid interference from other GNSS satellites, whereas mitigation techniques are essential to keep GNSS-R instruments working under external RFI degradation.

DME/TACAN Impact Analysis on GNSS Reflectometry

Global navigation satellite system reflectometry (GNSS-R) is becoming a widely accepted technique for remote sensing. The interferometric technique (iGNSS-R) correlates the direct signal received from a satellite and the same signal reflected on the Earths surface, whereas the conventional technique (cGNSS-R) correlates the reflected signal with a locally generated replica of the transmitted code. As GNSS signals are received below the noise level, this technique is extremely sensitive to radio frequency interference. The distance measurement equipment, and the TACtical air navigation systems are two radio navigation systems that transmit in the GPS L5, and Galileo E5 bands with powers up to 3.5 kW. This work studies in depth the impact of these systems on iGNSS-R, and cGNSS-R instruments. This study is then applied to a hypothetical reflectometer that will be placed in the international space station: The GEROS experiment. It is shown that the received power in space will be strong enough to degrade the systems performance by increasing the noise floor, but the sea altimetry precision will still be accurate enough for scientific studies.

Assessment of back-end RFI mitigation techniques in passive remote sensing

Radio-Frequency Interference (RFI) is a growing problem specially for those systems that work with low power signals such as passive remote sensing instruments. Consequently, RFI mitigation techniques are currently under development. This works aims at evaluating back-end mitigation algorithms in terms of their probability of detection and mitigation performance. Results show that Wavelet Denoising (WD), and Multiresolution Fourier Transform (MFT) are the best techniques in most scenarios, specially for GNSS-based instruments.

Soil Moisture mapping using forward scattered GPS L1 signals

This work presents a novel technique for the determination of soil moisture obtaining 2-D Soil Moisture (SM) information with a single instrument. Both the instrument and the retrieval algorithm used, which is based on inferring the reflection coefficient of the terrain by direct and forward scattering polarimetric measurements of Global Navigation Satellite Systems (GNSS) Signals, are briefly described. Some preliminary results of a field campaign performed on La Pobla de Mafumet (Tarragona, Spain) are presented. This instrument and retrieval algorithm can be used for different applications, such as, an input for the irrigation algorithm (Smart-Irrigation) or forest fire prevention among others.

Sea Ice Detection Using U.K. TDS-1 GNSS-R Data

A sea ice detection algorithm developed using the U.K. TechDemoSat-1 (U.K. TDS-1) global navigation satellite systems (GNSSs)-reflectometry data over the Arctic and Antarctic regions is presented. It is based on measuring the similarity of the received GNSS reflected waveform or delay Doppler map (DDM) to the coherent reflection model waveform. Over the open ocean, the scattered signal has a diffusive, incoherent nature; it is described by the rough surface scattering model based on the geometric optics and the Gaussian statistics for the ocean surface slopes. Over sea ice and, in particular, newly formed sea ice, the scattered signal acquires a coherence, which is characteristic for a surface with large flat areas. In order to measure the similarity of the received waveform or DDM, to the coherent reflection model, three different estimators are presented: the normalized DDM average, the trailing edge slope (TES), and the matched filter approach. Here, a probabilistic study is presented based on a Bayesian approach using two different and independent ground-truth data sets. This approach allows one to thoroughly assess the performance of the estimators. The best results are achieved for both the TES and the matched filter approach with a probability of detection of 98.5%, a probability of false alarm of ~ 3.6%, and a probability of error of 2.5%. However, the matched filter approach is preferred due to its simplicity. Data from AMSR2 processed using the Arctic Radiation and Turbulence Interaction STudy Sea Ice algorithm and from an Special Sensor Microwave Imager/Sounder radiometer processed by Ocean and Sea Ice SAF have been used as ground truth. A pixel has been classified as a sea ice pixel if the sea ice concentration (SIC) in it was larger than 15%. The measurement of the SIC is also assessed in this paper, but the nature of the U.K. TDS-1 data (lack of calibrated data) does not allow to make any specific conclusions about the SIC.

On the Correlation Between GNSS-R Reflectivity and L-Band Microwave Radiometry

This work compares microwave radiometry and global navigation satellite systems-reflectometry (GNSS-R) observations using data gathered from airborne flights conducted for three different soil moisture conditions. Two different regions are analyzed, a crops region and a grassland region. For the crops region, the correlation with the I/2 (first Stokes parameter divided by two) was between 0.74 and 0.8 for large incidence angle reflectivity data (30°-50°), while it was between 0.51 and 0.61 for the grassland region and the same incidence angle conditions. For the crops region, the correlation with the I/2 was between 0.64 and 0.69 for lower incidence angle reflectivity data (<;30°), while it was between 0.41 and 0.6 for the grassland region. This indicates that for large incidence angles the coherent scattering mechanism is dominant, while the lower incidence angles are more affected by incoherent scattering. Also a relationship between the reflectivity and the polarization index (PI) is observed. The PI has been used to remove surface roughness effects, but due to its dependence on the incidence angle only the large incidence angle observations were useful. The difference in ground resolution between microwave radiometry and GNSS-R and their strong correlation suggests that they might be combined to improve the spatial resolution of microwave radiometry measurements in terms of brightness temperature and consequently soil moisture retrievals.