First results are presented for ocean surface wind speed retrieval from reflected GPS signals measured by the low Earth orbiting UK TechDemoSat‐1 satellite (TDS‐1). Launched in July 2014, TDS‐1 provides the first new spaceborne Global Navigation Satellite System‐Reflectometry (GNSS‐R) data since the pioneering UK‐Disaster Monitoring Mission (UK‐DMC) experiment in 2003. Examples of onboard‐processed delay‐Doppler maps reveal excellent data quality for winds up to 27.9 m/s. Collocated Advanced Scatterometer (ASCAT) winds are used to develop and evaluate a wind speed algorithm based on signal‐to‐noise ratio (SNR) and the bistatic radar equation. For SNRs greater than 3 dB, wind speed is retrieved without bias and a precision around 2.2 m/s between 3 and 18 m/s even without calibration. Exploiting lower SNR signals, however, requires good knowledge of the antenna beam, platform attitude, and instrument gain setting. This study demonstrates the capabilities of low‐cost, low‐mass, and low‐power GNSS‐R receivers ahead of their launch on the NASA Cyclone GNSS (CYGNSS) constellation in 2016.

Abstract-We will show that ocean-reflected signals from the global positioning system (GPS) navigation satellite constellation can be detected from a low-earth orbiting satellite and that these signals show rough correlation with independent measurements of the sea winds. We will present waveforms of ocean-reflected GPS signals that have been detected using the experiment onboard the United Kingdom's Disaster Monitoring Constellation satellite and describe the processing methods used to obtain their delay and Doppler power distributions. The GPS bistatic radar experiment has made several raw data collections, and reflected GPS signals have been found on all attempts. The down linked data from an experiment has undergone extensive processing, and ocean-scattered signals have been mapped across a wide range of delay and Doppler space revealing characteristics which are known to be related to geophysical parameters such as surface roughness and wind speed. Here we will discuss the effects of integration time, reflection incidence angle and examine several delay-Doppler signal maps. The signals detected have been found to be in general agreement with an existing model (based on geometric optics) and with limited independent measurements of sea winds; a brief comparison is presented here. These results demonstrate that the concept of using bistatically reflected global navigation satellite systems signals from low earth orbit is a viable means of ocean remote sensing.

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

A simple empirical model is proposed to retrieve wave period from Ku‐band radar altimeter backscatter and significant wave height. The model formulation is heuristic, and fitted using a large dataset of collocated Topex altimeter and buoys measurements. Empirical models are proposed for the zero up‐crossing, the mean and the peak wave period, and compared with models by Davies et al. [1997] and Hwang et al. [1998]. Their performance is assessed using an independent validation dataset, and gives a retrieval error of 0.8s. Regional analysis indicates that the wave period models perform better in wind seas than in swell‐dominated conditions.