Information retrieval from spaceborne GNSS Reflectometry observations using physics- and learning-based techniques

This dissertation proposes a learning-based, physics-aware soil moisture (SM) retrieval algorithm for NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission. The proposed methodology has been built upon the literature review, analyses, and findings from a number of published studies throughout the dissertation research. Namely, a Sig- nals of Opportunity Coherent Bistatic scattering model (SCoBi) has been first developed at MSU and then its simulator has been open-sourced. Simulated GNSS-Reflectometry (GNSS-R) analyses have been conducted by using SCoBi. Significant findings have been noted such that (1) Although the dominance of either the coherent reflections or incoher- ent scattering over land is a debate, we demonstrated that coherent reflections are stronger for flat and smooth surfaces covered by low-to-moderate vegetation canopy; (2) The influ- ence of several land geophysical parameters such as SM, vegetation water content (VWC), and surface roughness on the bistatic reflectivity was quantified, the dynamic ranges of reflectivity changes due to SM and VWC are much higher than the changes due to the surface roughness. Such findings of these analyses, combined with a comprehensive lit- erature survey, have led to the present inversion algorithm: Physics- and learning-based retrieval of soil moisture information from space-borne GNSS-R measurements that are taken by NASA’s CYGNSS mission. The study is the first work that proposes a machine learning-based, non-parametric, and non-linear regression algorithm for CYGNSS-based soil moisture estimation. The results over point-scale soil moisture observations demon- strate promising performance for applicability to large scales. Potential future work will be extension of the methodology to global scales by training the model with larger and diverse data sets

Review of the CALIMAS Team Contributions to European Space Agency's Soil Moisture and Ocean Salinity Mission Calibration and Validation

Camps, Adriano ... et al.-- 38 pages, 22 figuresThis work summarizes the activities carried out by the SMOS (Soil Moisture and Ocean Salinity) Barcelona Expert Center (SMOS-BEC) team in conjunction with the CIALE/Universidad de Salamanca team, within the framework of the European Space Agency (ESA) CALIMAS project in preparation for the SMOS mission and during its first year of operation. Under these activities several studies were performed, ranging from Level 1 (calibration and image reconstruction) to Level 4 (land pixel disaggregation techniques, by means of data fusion with higher resolution data from optical/infrared sensors). Validation of SMOS salinity products by means of surface drifters developed ad-hoc, and soil moisture products over the REMEDHUS site (Zamora, Spain) are also presented. Results of other preparatory activities carried out to improve the performance of eventual SMOS follow-on missions are presented, including GNSS-R to infer the sea state correction needed for improved ocean salinity retrievals and land surface parameters. Results from CALIMAS show a satisfactory performance of the MIRAS instrument, the accuracy and efficiency of the algorithms implemented in the ground data processors, and explore the limits of spatial resolution of soil moisture products using data fusion, as well as the feasibility of GNSS-R techniques for sea state determination and soil moisture monitoringThis work has been performed under research grants TEC2005-06863-C02-01/TCM, ESP2005-06823-C05, ESP2007-65667-C04, AYA2008-05906-C02-01/ESP and AYA2010-22062-C05 from the Spanish Ministry of Science and Innovation, and a EURYI 2004 award from the European Science FoundationPeer Reviewe

Exploring bistatic scattering modeling for land surface applications using radio spectrum recycling in the Signal of Opportunity Coherent Bistatic Simulator

The potential for high spatio-temporal resolution microwave measurements has urged the adoption of the signals of opportunity (SoOp) passive radar technique for use in remote sensing. Recent trends in particular target highly complex remote sensing problems such as root-zone soil moisture and snow water equivalent. This dissertation explores the continued open-sourcing of the SoOp coherent bistatic scattering model (SCoBi) and its use in soil moisture sensing applications. Starting from ground-based applications, the feasibility of root-zone soil moisture remote sensing is assessed using available SoOp resources below L-band. A modularized, spaceborne model is then developed to simulate land-surface scattering and delay-Doppler maps over the available spectrum of SoOp resources. The simulation tools are intended to provide insights for future spaceborne modeling pursuits

GNSS transpolar earth reflectometry exploriNg system (G-TERN): mission concept

The global navigation satellite system (GNSS) Transpolar Earth Reflectometry exploriNg system (G-TERN) was proposed in response to ESA's Earth Explorer 9 revised call by a team of 33 multi-disciplinary scientists. The primary objective of the mission is to quantify at high spatio-temporal resolution crucial characteristics, processes and interactions between sea ice, and other Earth system components in order to advance the understanding and prediction of climate change and its impacts on the environment and society. The objective is articulated through three key questions. 1) In a rapidly changing Arctic regime and under the resilient Antarctic sea ice trend, how will highly dynamic forcings and couplings between the various components of the ocean, atmosphere, and cryosphere modify or influence the processes governing the characteristics of the sea ice cover (ice production, growth, deformation, and melt)? 2) What are the impacts of extreme events and feedback mechanisms on sea ice evolution? 3) What are the effects of the cryosphere behaviors, either rapidly changing or resiliently stable, on the global oceanic and atmospheric circulation and mid-latitude extreme events? To contribute answering these questions, G-TERN will measure key parameters of the sea ice, the oceans, and the atmosphere with frequent and dense coverage over polar areas, becoming a “dynamic mapper”of the ice conditions, the ice production, and the loss in multiple time and space scales, and surrounding environment. Over polar areas, the G-TERN will measure sea ice surface elevation (<;10 cm precision), roughness, and polarimetry aspects at 30-km resolution and 3-days full coverage. G-TERN will implement the interferometric GNSS reflectometry concept, from a single satellite in near-polar orbit with capability for 12 simultaneous observations. Unlike currently orbiting GNSS reflectometry missions, the G-TERN uses the full GNSS available bandwidth to improve its ranging measurements. The lifetime would be 2025-2030 or optimally 2025-2035, covering key stages of the transition toward a nearly ice-free Arctic Ocean in summer. This paper describes the mission objectives, it reviews its measurement techniques, summarizes the suggested implementation, and finally, it estimates the expected performance.Peer ReviewedPostprint (published version

Remote Sensing of Forest Biomass Using GNSS Reflectometry

In this study, the capability of Global Navigation Satellite System Reflectometry in evaluating forest biomass from space has been investigated by using data coming from the TechDemoSat-1 (TDS-1) mission of Surrey Satellite Technology Ltd. and from the Cyclone Satellite System (CyGNSS) mission of NASA. The analysis has been first conducted using TDS-1 data on a local scale, by selecting five test areas located in different parts of the Earth's surface. The areas were chosen as examples of various forest coverages, including equatorial and boreal forests. Then, the analysis has been extended by using CyGNSS to a global scale, including any type of forest coverage. The peak of the Delay Doppler Map calibrated to retrieve an "equivalent" reflectivity has been exploited for this investigation and its sensitivity to forest parameters has been evaluated by a direct comparison with vegetation optical depth (VOD) derived from the Soil Moisture Active Passive L-band radiometer, with a pantropical aboveground biomass (AGB) map and then with a tree height (H) global map derived from the Geoscience Laser Altimeter System installed on-board the ICEsat satellite. The sensitivity analysis confirmed the decreasing trend of the observed equivalent reflectivity for increasing biomass, with correlation coefficients 0.31 ≤ R ≤ 0.54 depending on the target parameter (VOD, AGB, or H) and on the considered dataset (local or global). These correlations were not sufficient to retrieve the target parameters by simple inversion of the direct relationships. The retrieval has been therefore based on Artificial Neural Networks making it possible to add other inputs (e.g., the incidence angle, the signal to noise ratio, and the lat/lon information in case of global maps) to the algorithm. Although not directly correlated to the biomass, these inputs helped in improving the retrieval accuracy. The algorithm was tested on both the selected areas and globally, showing a promising ability to retrieve the target parameter, either AGB or H, with correlation coefficients R ≃ 0.8

Temporal variability of GNSS-Reflectometry ocean wind speed retrieval performance during the UK TechDemoSat-1 mission

This paper presents the temporal evolution of Global Navigation Satellite System Reflectometry (GNSS-R) ocean wind speed retrieval performance during three years of the UK TechDemoSat-1 (TDS-1) mission. TDS-1 was launched in July 2014 and provides globally distributed spaceborne GNSS-R data over a lifespan of over three years, including several months of 24/7 operations. TDS-1 wind speeds are computed using the NOC Calibrated Bistatic Radar Equation algorithm version 0.5 (C-BRE v0.5), and are evaluated against ERA5 high resolution re-analysis data over the period 2015–2018. Analyses reveal significant temporal variability in TDS-1 monthly wind speed retrieval performance over the three years, with the best performance (~2 m∙s−1) achieved in the early part of the mission (May 2015). The temporal variability of retrieval performance is found to be driven by several non-geophysical factors, including TDS-1 platform attitude uncertainty and spatial/temporal changes in GPS transmit power from certain satellites. Evidence is presented of the impact of the GPS Block IIF Flex mode on retrieved GNSS-R wind speed after January 2017, which results in significantly underestimated ocean winds over a large region covering the North Atlantic, northern Indian Ocean, the Mediterranean, the Black Sea, and the Sea of Okhotsk. These GPS transmit power changes are shown to induce large negative wind speed biases of up to 3 m∙s−1. Analyses are also presented of the sensitivity of TDS-1 wind speed retrieval to platform attitude uncertainty using statistical simulations. It is suggested that a 4° increase in attitude uncertainty can produce up to 1 m∙s−1 increase in RMSE, and that TDS-1 attitude data do not fully reflect actual platform attitude. We conclude that the lack of knowledge about the GNSS-R nadir antenna gain map and TDS-1 platform-attitude limits the ability to determine the achievable wind speed retrieval performance with GNSS-R on TDS-1. The paper provides recommendations that accurate attitude knowledge and a good characterisation of GNSS-R nadir antenna patterns should be prioritised for future GNSS-R missions

GNSS reflectometry for land remote sensing applications

Soil moisture and vegetation biomass are two essential parameters from a scienti c and economical point of view. On one hand, they are key for the understanding of the hydrological and carbon cycle. On the other hand, soil moisture is essential for agricultural applications and water management, and vegetation biomass is crucial for regional development programs. Several remote sensing techniques have been used to measure these two parameters. However, retrieving soil moisture and vegetation biomass with the required accuracy, and the appropriate spatial and temporal resolutions still remains a major challenge. The use of Global Navigation Satellite Systems (GNSS) reflected signals as sources of opportunity for measuring soil moisture and vegetation biomass is assessed in this PhD Thesis. This technique, commonly known as GNSS-Reflectometry (GNSS-R), has gained increasing interest among the scienti c community during the last two decades due to its unique characteristics. Previous experimental works have already shown the capabilities of GNSS-R to sense small reflectivity changes on the surface. The use of the co- and cross-polarized reflected signals was also proposed to mitigate nuisance parameters, such as soil surface roughness, in the determination of soil moisture. However, experimental evidence of the suitability of that technique could not be demonstrated. This work analyses from a theoretical and an experimental point of view the capabilities of polarimetric observations of GNSS reflected signals for monitoring soil moisture and vegetation biomass. The Thesis is structured in four main parts. The fi rst part examines the fundamental aspects of the technique and provides a detailed review of the GNSS-R state of the art for soil moisture and vegetation monitoring. The second part deals with the scattering models from land surfaces. A comprehensive description of the formation of scattered signals from rough surfaces is provided. Simulations with current state of the art models for bare and vegetated soils were performed in order to analyze the scattering components of GNSS reflected signals. A simpli ed scattering model was also developed in order to relate in a straightforward way experimental measurements to soil bio-geophysical parameters. The third part reviews the experimental work performed within this research. The development of a GNSS-R instrument for land applications is described, together with the three experimental campaigns carried out in the frame of this PhD Thesis. The analysis of the GNSS-R and ground truth data is also discussed within this part. As predicted by models, it was observed that GNSS scattered signals from natural surfaces are a combination of a coherent and an incoherent scattering components. A data analysis technique was proposed to separate both scattering contributions. The use of polarimetric observations for the determination of soil moisture was demonstrated to be useful under most soil conditions. It was also observed that forests with high levels of biomass could be observed with GNSS reflected signals. The fourth and last part of the Thesis provides an analysis of the technology perspectives. A GNSS-R End-to-End simulator was used to determine the capabilities of the technique to observe di erent soil reflectivity conditions from a low Earth orbiting satellite. It was determined that high accuracy in the estimation of reflectivity could be achieved within reasonable on-ground resolution, as the coherent scattering component is expected to be the predominant one in a spaceborne scenario. The results obtained in this PhD Thesis show the promising potential of GNSS-R measurements for land remote sensing applications, which could represent an excellent complementary observation for a wide range of Earth Observation missions such as SMOS, SMAP, and the recently approved ESA Earth Explorer Mission Biomass.La humedad del suelo y la biomasa de la vegetaci on son dos parametros clave desde un punto de vista tanto cient co como econ omico. Por una parte son esenciales para el estudio del ciclo del agua y del carbono. Por otra parte, la humedad del suelo es esencial para la gesti on de las cosechas y los recursos h dricos, mientras que la biomasa es un par ametro fundamental para ciertos programas de desarrollo. Varias formas de teledetección se han utilizado para la observaci on remota de estos par ametros, sin embargo, su monitorizaci on con la precisi on y resoluci on necesarias es todav a un importante reto tecnol ogico. Esta Tesis evalua la capacidad de medir humedad del suelo y biomasa de la vegetaci on con señales de Sistemas Satelitales de Posicionamiento Global (GNSS, en sus siglas en ingl es) reflejadas sobre la Tierra. La t ecnica se conoce como Reflectometr í a GNSS (GNSS-R), la cual ha ganado un creciente inter es dentro de la comunidad científ ca durante las dos ultimas d ecadas. Experimentos previos a este trabajo ya demostraron la capacidad de observar cambios en la reflectividad del terreno con GNSS-R. El uso de la componente copolar y contrapolar de la señal reflejada fue propuesto para independizar la medida de humedad del suelo de otros par ametros como la rugosidad del terreno. Sin embargo, no se pudo demostrar una evidencia experimental de la viabilidad de la t ecnica. En este trabajo se analiza desde un punto de vista te orico y experimental el uso de la informaci on polarim etrica de la señales GNSS reflejadas sobre el suelo para la determinaci on de humedad y biomasa de la vegetaci on. La Tesis se estructura en cuatro partes principales. En la primera parte se eval uan los aspectos fundamentales de la t ecnica y se da una revisi on detallada del estado del arte para la observaci on de humedad y vegetaci on. En la segunda parte se discuten los modelos de dispersi on electromagn etica sobre el suelo. Simulaciones con estos modelos fueron realizadas para analizar las componentes coherente e incoherente de la dispersi on de la señal reflejada sobre distintos tipos de terreno. Durante este trabajo se desarroll o un modelo de reflexi on simpli cado para poder relacionar de forma directa las observaciones con los par ametros geof sicos del suelo. La tercera parte describe las campañas experimentales realizadas durante este trabajo y discute el an alisis y la comparaci on de los datos GNSS-R con las mediciones in-situ. Como se predice por los modelos, se comprob o experimentalmente que la señal reflejada est a formada por una componente coherente y otra incoherente. Una t ecnica de an alisis de datos se propuso para la separacióon de estas dos contribuciones. Con los datos de las campañas experimentales se demonstr o el bene cio del uso de la informaci on polarim etrica en las señales GNSS reflejadas para la medici on de humedad del suelo, para la mayor a de las condiciones de rugosidad observadas. Tambi en se demostr o la capacidad de este tipo de observaciones para medir zonas boscosas densamente pobladas. La cuarta parte de la tesis analiza la capacidad de la t ecnica para observar cambios en la reflectividad del suelo desde un sat elite en orbita baja. Los resultados obtenidos muestran que la reflectividad del terreno podr a medirse con gran precisi on ya que la componente coherente del scattering ser a la predominante en ese tipo de escenarios. En este trabajo de doctorado se muestran la potencialidades de la t ecnica GNSS-R para observar remotamente par ametros del suelo tan importantes como la humedad del suelo y la biomasa de la vegetaci on. Este tipo de medidas pueden complementar un amplio rango de misiones de observaci on de la Tierra como SMOS, SMAP, y Biomass, esta ultima recientemente aprobada para la siguiente misi on Earth Explorer de la ESA

Contributions to land, sea, and sea ice remote sensing using GNSS-reflectometry

This PhD thesis researches the use of passive remote sensing techniques using signals transmitted from the navigation satellites (GNSS) in order to retrieve different geophysical parameters. The thesis consists of two different parts without taking into account the introduction, the state of the art and the conclusions. The first part analyzes the Interference Pattern Technique (IPT), which was previously used in another PhD thesis, and proposes some key improvements. First, the addition of horizontal polarization to the existing vertical polarization is proposed. Then, the retrieval of soil moisture is studied using the horizontal polarization only and combining both polarizations to correct for the surface roughness effects. It is also demonstrated that the phase difference between the two interference patterns is directly related to soil moisture content. A field campaign was conducted in Australia to test empirically all the theoretical developments and algorithms. Secondly, the possibility of measuring Significant Wave Height (SWH) and Mean Sea Surface Level (MSSL) using the IPT is studied. A three month field campaign over coastal sea is devoted to that study. The SWH retrieval is a new estimation algorithm based on measuring the point where the interference pattern loses coherence. The MSSL retrieval is based on the estimation of the IPT oscillation frequency, testing different spectral estimators to improve the accuracy. Since the IPT is limited in coverage due to its static requirements, the research conducted in this thesis migrated to scatterometric GNSS-R techniques. The main goal that migration was to increase coverage of the different GNSS-R instruments. Therefore, the second part of this thesis analyzes the applicability of a scatterometric technique from different platforms: ground-based (mobile and fixed), airborne, and spaceborne. The ground-based still platforms have allowed to develop a soil moisture retrieval algorithm. The ground-based moving platforms have extended the validity of that algorithm. Airborne platforms have been used to study the reflected electric field statistics when the surface reflecting surface is varying (smooth or rough land, and sea). They have also been used to develop different algorithms to measure the coherent and incoherent scattered components depending on the data structure (real-data or complex data). Coherent reflectivity measured from airborne platforms has been compared to other techniques such microwave radiometry, which is highly used in the soil moisture retrieval from spaceborne sensors, and other sensors using optical, multispectral and thermal frequency bands. These relationships between microwave radiometry and GNSS-R measurements suggests the potential synergy of both techniques. A sea ice detection algorithm is also developed using scatterometric GNSS-R data from the UK TDS-1 mission. This algorithm is based on measuring the degree of coherence of the reflected waveform. Finally, a field campaign was conducted to study the effect of vegetation on the GNSS signals that pass through it in order to take into account and correct the effect of vegetation in the GNSS-R data and in the soil moisture retrieval algorithms.Aquesta tesi doctoral aprofundeix en el coneixement de les tècniques de teledetecció passives utilitzant senyals emesos pels satèl·lits de navegació (GNSS) amb l'objectiu de recuperar diferents paràmetres geofísics del terreny. La tesi conté dues parts ben diferenciades a banda de la introducció, estat de l'art i conclusions. La primera part analitza la tècnica coneguda com a patró d'interferències, utilitzada prèviament en una altra tesi doctoral, i proposa certes millores per la seva aplicabilitat. En primer lloc es decideix afegir polarització horitzontal a la ja existent polarització vertical, i s'estudia la recuperació d'humitat del sòl utilitzant només polarització horitzontal i combinant les dues polaritzacions per corregir els efectes de la rugositat del terreny. A continuació es demostra que la mesura de desfasament entre els dos patrons d'interferència està directament relacionada amb la humitat del terreny. Es va realitzar una campanya de mesures a Austràlia per provar empíricament tots els desenvolupaments teòrics i algorismes proposats. En segon lloc s'analitza l'aplicabilitat del patró d'interferències en la mesura de l'altura de les onades (SWH) i del nivell del mar (MSSL), tots dos de forma precisa. L'estimació de l'alçada de les onades és un procés totalment nou basat en mesurar el punt on el patró d'interferències perd la coherència. L'estimació del nivell del mar es basa en l'anàlisi espectral del patró d'interferències provant diferents estimadors espectrals. Atès que la tècnica del patró d'interferència està limitada en cobertura per les seves característiques estàtiques, la investigació duta a terme en aquesta tesi doctoral va migrar cap a tècniques GNSS-R escateromètriques. El principal objectiu a assolir va ser el d'augmentar la cobertura dels diferents instruments GNSS-R de mesura. En conseqüència, la segona part d'aquesta tesi analitza l'aplicabilitat d'aquestes tècniques des de diferents plataformes terrestres (mòbils i fixes), aerotransportades i satèl·lit. Les plataformes terrestres fixes han permès derivar algoritmes de recuperació d'humitat i les mòbils estendre la validació d'aquests. Les plataformes aerotransportades s'han utilitzat per mirar l'estadística del camp elèctric reflectit quan la superfície on es reflecteixen els senyals GNSS va variant (terra plana o terra rugosa, i mar). També han servit per desenvolupar diferents algorismes amb l'objectiu de determinar les components coherent i incoherent del senyal reflectit. De la mateixa manera, dades de reflectivitat coherent mesurades des d'aquestes plataformes han estat comparades amb altres tècniques de teledetecció passiva com la radiometria de microones, altament utilitzada en la mesura d'humitat de terreny, i altres sensors òptics, multi-espectrals, i tèrmics. Aquests resultats han permès suggerir la possible sinergia de dades d'ambdues tecnologies. Un algorisme per detectar la presència de gel sobre el mar també ha estat desenvolupat mitjançant l'ús de dades GNSS-R escateromètriques satel·litals de la missió UK TDS-1. Aquest algorisme es basa en mesurar el grau de coherència de la forma d'ona reflectida. Finalment, s'ha realitzat un estudi de l'efecte de la vegetació en els senyals GNSS que la travessen, per tal de poder corregir aquest efecte en els algoritmes de recuperació d'humitat del terreny

Engineering Calibration and Physical Principles of GNSS-Reflectometry for Earth Remote Sensing

The Cyclone Global Navigation Satellite System (CYGNSS) is a NASA mission that uses 32 Global Positioning System (GPS) satellites as active sources and 8 CYGNSS satellites as passive receivers to measure ocean surface roughness and wind speed, as well as soil moisture and flood inundation over land. This dissertation addresses two major aspects of engineering calibration: (1) characterization of the GPS effective isotropic radiated power (EIRP) for calibration of normalized bistatic radar cross section (NBRCS) observables; and (2) development of an end-to-end calibration approach using modeling and measurements of ocean surface mean square slope (MSS). To estimate the GPS transmit power, a ground-based GPS constellation power monitor (GCPM) system has been built to accurately and precisely measure the direct GPS signals. The transmit power of the L1 coarse/acquisition (C/A) code of the full GPS constellation is estimated using an optimal search algorithm. Updated values for transmit power have been successfully applied to CYGNSS L1B calibration and found to significantly reduce the PRN dependence of CYGNSS L1 and L2 data products. The gain pattern of each GPS satellite’s transmit antenna for the L1 C/A signal is determined from measurements of signal strength received by the 8-satellite CYGNSS constellation. Determination of GPS patterns requires knowledge of CYGNSS patterns and vice versa, so a procedure is developed to solve for both of them iteratively. The new GPS and CYGNSS patterns have been incorporated into the science data processing algorithm used by the CYGNSS mission and result in improved calibration performance. Variable transmit power by numerous Block IIF and IIR-M GPS space vehicles has been observed due to their flex power mode. Non-uniformity in the GPS antenna gain patterns further complicates EIRP estimation. A dynamic calibration approach is developed to further address GPS EIRP variability. It uses measurements by the direct received GPS signal to estimate GPS EIRP in the specular reflected direction and then incorporates them into the calibration of NBRCS. Dynamic EIRP calibration instantaneously detects and corrects for power fluctuations in the GPS transmitters and significantly reduces errors due to GPS antenna gain azimuthal asymmetry. It allows observations with the most variable Block IIF transmitters (approximately 37% of the GPS constellation) to be included in the standard data products and further improves the calibration quality of the NBRCS. A physics-based approach is then proposed to examine potential calibration errors and to further improve the Level 1 calibration. The mean square slope (mss) is a key physical parameter that relates the ocean surface properties (wave spectra) to the CYGNSS measurement of NBRCS. An approach to model the mss for validation with CYGNSS mss data is developed by adding the contribution of a high frequency tail to the WAVEWATCH III (WW3) mss. It is demonstrated that the ratio of CYGNSS mss to modified WW3 mss can be used to diagnose potential calibration errors that exist in the Level 1 calibration algorithm. This approach can help to improve CYGNSS data quality, including the Level 1 NBRCS and Level 2 ocean surface wind speed and roughness. The engineering calibration methods presented in this dissertation make significant contributions to the spatial coverage, calibration quality of the measured NBRCS and the geophysical data products produced by the NASA CYGNSS mission. The research is also useful to the system design, science investigation and engineering calibration of future GNSS-reflectometry missions.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168052/1/wangtl_1.pd