In traditional GNSS applications, signals arriving at a receiver's antenna from nearby reflecting surfaces (multipath) interfere with the signals received directly from the satellites which can often result in a reduction of positioning accuracy. About two decades ago researchers produced an idea to use reflected GNSS signals for remote-sensing applications. In this new concept a GNSS transmitter together with a receiver capable of processing GNSS scattered signals of opportunity becomes bistatic radar. By properly processing the scattered signal, this system can be configured either as an altimeter, or a scatterometer allowing us to estimate such characteristics of land or ocean surface as height, roughness, or dielectric properties of the underlying media. From there, using various methods the geophysical parameters can be estimated such as mesoscale ocean topography, ocean surface winds, soil moisture, vegetation, snowpack, and sea ice. Depending on the platform of the GNSS receiver (stationary, airborne, or spaceborne), the capabilities of this technique and specific methods for processing of the reflected signals may vary. In this tutorial, we describe this new remotesensing technique, discuss some of the interesting results that have been already obtained, and give an overview of current and planned spacecraft missions.

Abstract-In Earth observation programs there is a need of passive low frequency (L-band)

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Abstract-Global navigation satellite systems-reflectometry (GNSS-R) is an emerging remote sensing technique that makes use of navigation signals as signals of opportunity in a multistatic radar configuration, with as many transmitters as navigation satellites are in view. GNSS-R sensitivity to soil moisture has already been proven from ground-based and airborne experiments, but studies using space-borne data are still preliminary due to the limited amount of data, collocation, footprint heterogeneity, etc. This study presents a sensitivity study of TechDemoSat-1 GNSS-R data to soil moisture over different types of surfaces (i.e., vegetation covers) and for a wide range of soil moisture and normalized difference vegetation index (NDVI) values. Despite the scattering in the data, which can be largely attributed to the delay-Doppler maps peak variance, the temporal and spatial (footprint size) collocation mismatch with the SMOS soil moisture, and MODIS NDVI vegetation data, and land use data, experimental results for low NDVI values show a large sensitivity to soil moisture and a relatively good Pearson correlation coefficient. As the vegetation cover increases (NDVI increases) the reflectivity, the sensitivity to soil moisture and the Pearson correlation coefficient decreases, but it is still significant. Index Terms-Global

The ESA's Soil Moisture and Ocean Salinity (SMOS) mission is the first satellite devoted to measure the Earth's surface soil moisture. It has a spatial resolution of km and a 3-day revisit. In this paper, a downscaling algorithm is presented as a new ability to obtain multiresolution soil moisture estimates from SMOS using visible-to-infrared remotely sensed observations. This algorithm is applied to combine 2 years of SMOS and MODIS Terra/Aqua data over the Iberian Peninsula into fine-scale (1 km) soil moisture estimates. Disaggregated soil moisture maps are compared to 0-5 cm ground-based measurements from the REMEDHUS network. Three matching strategies are employed: 1) a comparison at 40 km spatial resolution is undertaken to ensure SMOS sensitivity is preserved in the downscaled maps; 2) the spatiotemporal correlation of downscaled maps is analyzed through comparison with point-scale observations; and 3) high-resolution maps and ground-based observations are aggregated per land-use to identify spatial patterns related with vegetation activity and soil type. Results show that the downscaling method improves the spatial representation of SMOS coarse soil moisture estimates while maintaining temporal correlation and root mean squared differences with ground-based measurements. The dynamic range of in situ soil moisture measurements is reproduced in the highresolution maps, including stations with different mean soil wetness conditions. Downscaled maps capture the soil moisture dynamics of general land uses, with the exception of irrigated crops. This evaluation study supports the use of this downscaling approach to enhance the spatial resolution of SMOS observations over semi-arid regions such as the Iberian Peninsula.

This paper revises the precision of altimetric measurements made with signals of the Global Navigation Satellite Systems (GNSS) reflected (GNSS-R) off the sea surface. In particular, we investigate the performance of two different GNSS-R techniques, referred to here as the clean-replica and interferometric approaches. The former has been used in GNSS-R campaigns since the late 1990s, while the latter has only been tested once, in 2010, from an 18-m-high bridge in static conditions and estuary waters. In 2011, we conducted an airborne experiment over the Baltic Sea at 3-km altitude to test the interferometric concept in dynamic and rougher conditions. The campaign also flew a clean-replica GNSS-R instrument with the purpose of comparing both approaches. We have analyzed with detail the data sets to extract and validate models of the noise present in both techniques. After predicting the noise models and verifying these with aircraft data, we used them to obtain the precision of altimetric measurements and to extrapolate the performance analysis to spaceborne scenarios. The main conclusions are that the suggested noise model agrees with measured data and that the GNSS-R interferometric technique is at least two times better in precision than a technique based on using a clean replica of the publicly available GPS code. This represents a factor of at least four times finer along-track resolution. A precision of 22 cm in 65-km along-track averaging should be achievable using near-nadir interferometric GNSS-R observations from a low earth orbiter.

1A sea ice detection algorithm developed using UK TDS-1 Global Navigation Satellite Systems (GNSS)- newly formed sea ice, the scattering is mostly coherent which is typical for a mostly flat surface. In order to 7 measure the degree of coherence of the received waveform or DDM three different estimators are presented: 8 the normalized DDM average, the Trailing Edge Slope (TES), and the matched filter approach. Here we present 9 a probabilistic study based on a Bayesian approach using two different and independent ground-truth datasets. 10This approach allow us thoroughly assessing the performance of the estimators. The best results are achieved 11 for both the TES and the matched filter approach with a probability of detection of 97%, a probability of false 12 alarm of ∼ 2%, and a probability of error of 2.5%. However, the matched filter approach is preferred due to 13 its simplicity. The measurement of the sea ice concentration is also assessed in this work, but the nature of the 14 UK TDS-1 data (lack of calibrated data) does not allow us to make any specific conclusions about the sea ice 15 concentration. 16 Index Terms 17Sea Ice, coherent scattering, incoherent scattering, GNSS-R, UK TDS-1 18

Abstract-The recent use of along-track interferometry (ATI) in synthetic aperture radar (SAR) has shown promise for synoptic measurement of ocean surface currents. ATI-SARs have been used to estimate wave fields, currents, and current features. This paper describes and analyzes a dual-beam along-track interferometer to provide spatially resolved vector surface velocity estimates with a single pass of an aircraft. The design employs a pair of interferometer beams, one squinted forward and one squinted aft. Each interferometric phase is sensitive to the component of surface Doppler velocity in the direction of the beam. Therefore, a proper combination of these measurements provides a vector surface velocity estimate in one pass of the aircraft. We find that precise measurements dictate widely spaced beams and that the spatial resolution for the squinted SAR is essentially identical to the sidelooking case. Practical instrument design issues are discussed, and an airborne system currently in development is described. Through computer simulation, we observe the azimuthal displacement of interferometric phases by moving surfaces identical to those of conventional SAR and find that such displacement can bias the estimated surface velocity.