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.

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.

The interference pattern technique (IPT) consists of the coherent addition of the direct and reflected global navigation satellite systems (GNSS) signals in the receiving antenna. The detected power oscillates (fading), and the amplitude of these oscillations is very sensitive to the soil reflection coefficient at the specular reflection point. Therefore, variations of the reflection coefficient can be mapped, and thus dielectric constant variations, from which soil moisture can be retrieved. This work extends the use of the IPT technique from vertical polarization (V-Pol) to horizontal polarization (H-Pol). Moreover, the IPT equations are reformulated to facilitate the combination of dual-polarization retrievals. Simulations of the interference patterns at V- and H-Pol are presented for different soil moisture conditions. An upgrade of the SMIGOL GNSS-R instrument for dual-polarization observations is presented. This instrument was deployed in a flat, dry grassland in Yanco, Australia, in order to validate the proposed concepts. Finally, a comparison between the data retrieved from the SMIGOL instrument and the ground-truth soil moisture data is presented showing a good agreement between them and rainfall information.

Global navigation satellite systems (GNSS) signals offer a promising opportunity to perform mesoscale altimetry with worldwide coverage using small satellites. However, unlike the signals used in classical altimeters, the GNSS signals have smaller bandwidth and lower transmitted power. This paper analyzes the achievable height precision of the Global Navigation Satellite System Reflectometry (GNSS-R) altimeters based on the Cramér-Rao bound for time-delay estimation. Precision bounds for the composite signals GPS L1 and L5 and Galileo E1, E5, and E6 in a spaceborne mission scenario are assessed, and the optimum receiver bandwidths which minimize them are obtained.

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 Politècnica 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).

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 Kingdom's Disaster Monitoring Constellation (UK-DMC) satellite.