This paper gives a summary of the HydroGNSS mission and status in the preparations up to launch. Some of the advancements in instrument are presented, including on-board gain adjustment, geolocation. Also the ground processing Payload Data Ground Segment is introduced and some of the processing advances, including antenna pattern modelling for EIRP estimation and bounding of measurement areas.

HydroGNSS is the second mission supported by the European Space Agency (ESA) under the Scout program, which is a new framework (3 years from KO to launch, cost ≤ 30 M€) by which ESA aims to demonstrate disruptive sensing techniques or incremental science, while retaining the potential to be subsequently scaled up in larger missions or implemented in future ESA Earth Observation programmes. HydroGNSS consists of a scientific demonstrator that primarily addresses land bio-geophysical variables. The mission is comprised of one satellite (with an option on the second) flying at a low-Earth orbit to collect Global Navigation Satellite System reflections (i.e., Delay Doppler Maps, DDMs) near continuously over the globe. The DDMs are used to generate Level 2 products related to Essential Climate Variables (ECV s), whose estimation defines the primary scientific goal of the mission. In this contribution we outline a review of the ECVs targeted by HydroGNSS, showing some representative results achieved during preliminary studies about the mission. Special emphasis is given to the monitoring of soil freeze-thaw state and soil moisture. ECVs are of great interest and support the sustainable development agenda adopted by the United Nations members in 2015.

Monitoring freeze/thaw variations of the Earth surfaces is of paramount importance for the study of biogeochemical processes and climate change. At present, the use of passive sensors is well established, but, very recently, some studies demonstrated the potentialities of observations exploiting signals of opportunity. We propose here an advanced study to demonstrate the capability of spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) to provide accurate and systematic information about the Earth-surface freeze/thaw state. Reflectivity values derived from TechDemoSat-1 (TDS-1) data are elaborated and compared against the Soil Moisture and Ocean Salinity (SMOS) freeze/thaw product, while state-of-the-art land cover data are used to select GNSS-R data within an estimated footprint. In spite of the limited data availability due to sparse spatial coverage and calibration issues of TDS-1 observations, the proposed analysis demonstrates the possibility of monitoring the freeze/thaw state by analyzing the calibrated reflectivity, including also the possibility of detecting the transition state between frozen and thawed conditions across seasonal variations. This feature makes the design of next-generation GNSS-R satellite missions a unique opportunity to achieve high-resolution freeze/thaw monitoring with small and low-cost platforms.

GNSS reflectometry, whilst originally envisaged for ocean wind speed sensing, has recently been shown to be sensitive to land parameters such as soil moisture. Soil moisture is an important variable for many use cases including climate change monitoring, and as such there is a need to reduce gaps in datasets of this variable collected by satellites. By implementation on small platforms, GNSS-R missions can address this need, but current instrumentation must be updated to allow prediction of reflection points over the land surface. This paper presents an algorithm for achieving this along with results from both software testing and initial on-board implementation on DoT-1. These show that when Delay-Doppler maps are generated using the new algorithm the peak reflected power is successfully captured (in line with platform constraints) in 55% of software tests, compared with just 10% for the current method. Telemetry from DoT-1 shows that the algorithm has been successfully incorporated into the flight software. Future tasks to verify the on-board performance and improve the algorithm further are also discussed.

Monitoring freeze/thaw variations of the Earth surfaces is of great value for the study of biogeochemical processes and climate changes. Over the last decade, the use of passive sensors has been established and, more recently, some researches demonstrated the potential of exploiting observations based on signals of opportunity. We propose an advanced study to assess the capability of spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) to give systematic information about the soil freeze/thaw state of high-latitude regions. To this aim, reflectivity values derived from TechDemoSat-1 (TDS-1) data are elaborated using state-of-art land cover data.

GNSS Reflectometry has been developing rapidly as an L-Band remote sensing technology suitable for small satellites and continues to find applications over ocean, ice and land. The TDS-1 [1] and CYGNSS missions [2] were primarily flown to target wind speed over the ocean but subsequently enabled demonstration of the potential for cryospheric and hydrological applications. The proposed HydroGNSS ESA Scout mission concept [3] has been developed to address land-based hydrological essential climate variables, specifically soil moisture, inundation, freeze / thaw state and biomass, as required by GCOS [4]. New techniques anticipated for HydroGNSS include the use of Galileo signals, coherent reflection sensing, dual polarisation and dual frequency reflectometry exploration.

In February 2019 a Project Authorization Request was approved by the Institute of Electrical and Electronics Engineers (IEEE) Standards Association with the title “Standard for Global Navigation Satellite System Reflectometry (GNSS-R) Data and Metadata Content”. A Working Group has been assembled to draft this standard with the purpose of unifying and documenting GNSS-R measurements, calibration procedures, and product level definitions. The Working Group (http://www.grss-ieee.org/community/technical-committees/standards-or-earth-observations/) includes members, collaborators, and contributors from academia, international space agencies, and private industry. In a recent face-to-face meeting held during the ARSI+KEO 2019 Conference, the need was recognized to develop a standard with a wide range of operations, providing procedure guidelines independently of constraints imposed by current limitations on geophysical parameters retrieval algorithms. As such, this effort aims to establish the fundamentals of a potential virtual network of satellites providing inter-comparable data to the scientific community.

Global Navigation Satellite System-Reflectometry (GNSS-R) is an innovative and rapidly developing approach to Earth Observation that makes use of signals of opportunity from GNSS, which have been reflected off the Earth's surface. This technology has been demonstrated to be applicable to the remote sensing of a number of geophysical surface parameters including ocean wind speed and sea-ice. Using data collected by the UK TechDemoSat-1 mission between 2014 and 2018, the National Oceanography Centre (NOC) has developed a GNSS-R signal processing scheme called the NOC Calibrated Bistatic Radar Equation (C-BRE) processor that features an ocean wind speed inversion algorithm incorporating radiometric calibration submodules and several corrections steps that mitigate effects related to the GNSS system, instrumentm and geometry. The latest version of the NOC GNSS-R processor additionally features updated data quality control mechanisms that include the flagging of radio frequency interference (RFI) and sea-ice detection based on the GNSS-R waveform.

Research efforts have been turning in recent times to the use of Global Navigation Satellite System Reflectometry (GNSS-R) for sensing land parameters such as soil moisture and above ground biomass, which are essential for climate modelling. GNSS-R instrumentation to date has been designed with the purpose of sensing ocean parameters (e.g. wind speed). In order to enable operational, spaceborne GNSS-R missions for land-sensing, upgrades to instrumentation are required. One aspect is the prediction of reflection points, which over the land is affected by the presence of topography; a problem not encountered when predicting reflection points over the ocean. This paper presents an algorithm which enables accurate prediction of reflection points in areas of topography to enable real-time, on-board production of Delay-Doppler Maps of land reflected signals, a development which is critical for enabling operational land-sensing GNSS-R missions.

A fully polarimetric Airborne Wind Vector Scatterometer (AWVS) is developed to provide independent airborne wind vector measurements for validation of space-borne GNSS-R measurements. The scatterometer is designed to meet 1 m/s wind speed accuracy requirement. In this ad hoc and low-budget project, the instrument development exploited on some already existing subsystems. The development started from scientific system requirement definition and ended to two experiment flights for wind vector retrieval from three areas at the Gulf of Finland, the Baltic Sea. One of the flights was carried out with a simultaneous overpass of the TDS-l satellite, conducting the GNSS-R measurements. The results confirm the measurement capabilities of the GNSS-R technology and the desired 1 m/s wind speed accuracy of the developed scatterometer. Moreover, the fully polarimetric backscattering results support well other recent measurements and models of cross-polarized sea surface scattering.

In this paper we analyse the GPS signals reflected by the surface of the ocean to retrieve information about the sea surface roughness, expressed in statistical terms by means of the sea surface Mean Square Slopes (MSS). Particularly, we perform Delay-Doppler mapping of real scattered GPS signals from the Surrey Satellite Technolody Ltd UK-DMC mission, and we simulate Delay-Doppler Maps (DDMs) using the Zavorotny-Voronovich model of the GPS power scattered from the ocean surface, as a function of the geometrical properties of the transmitter and receiver, as well as statistical properties of the scattering surface. Subsequently, we fit simulated DDMs to the measured ones, to retrieve the optimal MSS of the scattering surface, and we compare GPS-derived MSS with theoretical and in situ MSS, calculated using the Elfouhaily et al. wave spectrum and co-located buoy spectra of the National Data Buoy Center (NDBC).

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.

A study has been undertaken by Surrey Satellite Technology Limited (SSTL) with support from the British National Space Centre (BNSC) to upgrade SSTL's Space GPS Receiver (SGR) into an ocean remote sensing instrument. Software algorithms were added to the SGR to permit on-board characterisation of GPS reflection opportunities. Subsequently, a hardware interface was added to allow for raw data sampling and in-depth data analysis. The upgraded SGR has undergone several levels of testing to date. The real time specular point calculations and an on board slewing capability were demonstrated using a Low Earth Orbit (LEO) spacecraft carrying an SGR for navigation purposes. The ability to map a reflected GPS signal was then accomplished during ground testing from an observatory on a hill above Barcelona, Spain. In preparing the instrument for an upcoming flight experiment, the raw data analysis capability has been undergoing substantial validation and optimisation. The ultimate goal of these experiments is to recover parameters relating to sea-state that may be useful for both scientific and commercial marine users. This paper is intended to detail the initial phases of development and testing of a future low cost ocean remote sensing instrument.