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.

The bistatic radar equation currently used for simulating surface-reflected waveforms or delay-Doppler maps (DDMs), produced by signals of opportunity from global navigation satellites system (GNSS) or communication satellites, was previously derived under some limiting assumptions. One of them was the use of the Kirchhoff approximation in a geometric optics limit that assumes strong diffuse (noncoherent) scattering typical for very rough surfaces. This equation would produce an incorrect result for the case of weak diffuse scattering, or in the presence of coherent reflection. In this paper, it is shown that the assumption of strong diffuse scattering is not necessary in deriving such an equation. The derivation of a generalized bistatic radar equation is now based only on the assumption of roughness statistics being spatially homogeneous, and thus this equation is applicable for a much wider range of surface conditions and scattering geometries. This approach allows to correctly describe the transition from partially coherent scattering to completely noncoherent, strong diffuse scattering. It is demonstrated for the case of the GNSS-R DDMs simulated for a wide range of surface winds, and their transitional behavior is discussed.

Many of the currently used models of scattering from a rough ocean surface are designed for the regime of strong diffuse scattering that takes place at large Rayleigh parameter Ra . Using them for the case of weak, or even moderate diffuse scattering that is characterized by Ra ≲ 1 would lead to an incorrect result. At the same time, for practical applications it is important to describe the transition from partially-coherent scattering to completely non-coherent, strong diffuse scattering in terms of the bistatic radar cross section σ0. This situation may occur for scattering of GNSS signals or other signals of opportunity from a rough ocean surface under weak winds, or from ice. In this paper, we obtain an expression for σ0 for the case of weak-to-moderate diffuse scattering using a formulation based on the small slope approximation of the first order (SSA1). For a reasonable range of Ra , calculations can be quickly performed using standard desktop computers. We demonstrate results of such calculations for bistatic radar scattering for L-band at lowto-moderate Ra and its transition to σ0 at large values of Ra.

This paper analyzes and compares multiple techniques for estimating the mean square slope (MSS) of surface waves during Hurricane Ike in the Gulf of Mexico and studies the correlation of the MSS estimates with wind speed measurements along the same tracks. Three separate instruments collected measurements in parallel, including a GPS reflectometry (GPS-R) receiver, a stepped frequency microwave radiometer (SFMR), and a wide swath radar altimeter (WSRA). These datasets were used to study the correlation between the flight level and near-surface wind and MSS during Hurricane Ike in 2008. The GPS-R, SFMR, and WSRA instruments recorded temporally and spatially coincident data during two passes over the hurricane eye. This paper estimates the ocean surface MSS using GPS-R for two eye transects using: a least squares model fitting technique, the reflected signal waveform width, and an integration of the reflected signals in an area around the peak. Subsequently, the correlations between the GPS-R and WSRA MSS estimates and the SFMR wind speed estimates are compared to reveal regions of high and low surface MSS to wind speed correlation. Finally, a relationship between wind and MSS was derived from the GPS-R and SFMR data and is compared to existing MSS/wind models, including the results obtained by Katzberg et al. for hurricane conditions.

Feasibility of sensing mesoscale ocean eddies using spaceborne Global Navigation Satellite Systems-Reflectometry (GNSS-R) measurements is demonstrated for the first time. Measurements of Cyclone GNSS (CYGNSS) satellite missions over the eddies, documented in the Aviso eddy trajectory atlas, are studied. The investigation reports on the evidence of normalized bistatic radar cross section ( ${\sigma }^0$ ) responses over the center or the edges of the eddies. A statistical analysis using profiles over eddies in 2017 is carried out. The potential contributing factors leaving the signature in the measurements are discussed. The analysis of GNSS-R observations collocated with ancillary data from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis-5 (ERA-5) shows strong inverse correlations of ${\sigma }^0$ with the sensible heat flux and surface stress in certain conditions.

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.