Estimativa da umidade do solo por refletometria GNSS : uma revisão conceitual

Soil moisture monitoring enables efficient management and use of water resources, having great importance for several purposes, such as: monitoring of risk areas; delimitation of areas susceptible to flooding; geotechnical activities; and in agriculture development. GNSS Reflectometry (GNSS-R) is a scientific and technological development that allows one to perform proximal or remote sensing, depending on the antenna height concerning the surface, by means of navigation satellites. This method exploits GNSS signals indirectly reaching a receiver antenna after they are reflected on the surrounding surfaces. In this method, direct and indirect GNSS signals that reach the receiving antenna are exploited, after reflection on the surfaces existing around the antenna. The combination of these two signals causes the multipath effect, which affects GNSS observable and deteriorates positioning. On the other hand, when interacting with these reflecting surfaces one can estimate their properties. One of the main advantages of GNSS-R, when compared with the conventional methods, is the intermediate coverage area, as well as, the use of the well-defined structure of GNSS systems that guarantee appropriate temporal resolution. The scope of this paper is to present a conceptual review of GNSS-R applied to soil moisture monitoring.O monitoramento da umidade do solo possibilita o manejo e uso eficiente de recursos hídricos, sendo uma atividade importante em diversas áreas, tais como: no monitoramento de áreas de risco; delimitação de áreas suscetíveis a enchentes; atividades da geotecnia; e na agricultura. A Refletometria GNSS (GNSS-R) é um desenvolvimento científico e tecnológico que permite realizar sensoriamento remoto ou proximal, a depender da altura da antena em relação à superfície, com satélites de navegação. Neste método, explora-se os sinais GNSS que chegam à antena receptora de maneira direta e indireta, após reflexão nas superfícies existentes no entorno da antena. A combinação destes dois sinais ocasiona o efeito de multicaminho, que afeta as observáveis GNSS e deteriora o posicionamento. Por outro lado, ao interagir com estas superfícies, o sinal indireto permite estimar atributos acerca destas superfícies, como por exemplo a umidade do solo. Uma das principais vantagens em relação aos métodos convencionais reside no fato do GNSS-R proporcionar uma área de abrangência intermediária e o uso da estrutura bem estabelecida dos satélites GNSS, que garantem resolução temporal apropriada. O escopo deste trabalho é apresentar uma revisão conceitual acerca do GNSS-R aplicado no monitoramento da umidade do solo

Contributions to GNSS-R earth remote sensing from nano-satellites

Premi extraordinari doctorat UPC curs 2015-2016, àmbit de CiènciesGlobal Navigation Satellite Systems Reflectometry (GNSS-R) is a multi-static radar using navigation signals as signals of opportunity. It provides wide-swath and improved spatio-temporal sampling over current space-borne missions. The lack of experimental datasets from space covering signals from multiple constellations (GPS, GLONASS, Galileo, Beidou) at dual-band (L1 and L2) and dual-polarization (Right Hand Left Hand Circular Polarization: RHCP and LHCP), over the ocean, land and cryosphere remains a bottleneck to further develop these techniques. 3Cat-2 is a 6 units (3 x 2 elementary blocks of 10 x 10 x 10 cm3) CubeSat mission ayming to explore fundamentals issues towards an improvement in the understanding of the bistatic scattering properties of different targets. Since geolocalization of specific reflections points is determined by the geometry only, a moderate pointing accuracy is still required to correct for the antena pattern in scatterometry measurements. 3Cat-2 launch is foreseen for the first quarter 2016 into a Sun-Synchronous orbit of 510 km height using a Long March II D rocket. This Ph.D. Thesis represents the main contributions to the development of the 3Cat-2 GNSS-R Earth observation mission (6U CubeSat) including a novel type of GNSS-R technique: the reconstructed one. The desing, development of the platform, and a number of ground-based, airborne and stratospheric balloon experiments to validate the technique and to optimize the instrument. In particular, the main contributions of this Ph.D. thesis are: 1) A novel dual-band Global Navigation Satellite Systems Reflectometer that uses the P(Y) and C/A signals scattered over the sea surface to perform highly precise altimetric measurements (PYCARO). 2) The first proof-of-concept of PYCARO was performed during two different ground-based field experiments over a dam and over the sea under different surface roughness conditions. 3) The scattering of GNSS signals over a water surface has been studied when the receiver is at low height, as for GNSS-R coastal altimetry applications. The precise determination of the local sea level and wave state from the coast can provide useful altimetry and wave information as "dry" tide and wave gauges. In order to test this concept an experiment has been conducted at the Canal d'Investigació i Experimentació Marítima (CIEM) wave channel for two synthetic "sea" states. 4) Two ESA-sponsored airborne experiments were perfomed to test the precision and the relative accuracy of the conventional GNSS-R. 5) The empirical results of a GNSS-R experiment on-board the ESA-sponsored BAXUS 17 stratospheric balloon campaign performed North of Sweden over boreal forests showed that the power of the reflected signals is nearly independent of the platform height for a high coherent integration time. 6) An improved version of the PYCARO payload was tested in Octover 2014 for the second time during the ESA-sposored BEXUS-19,. This work achieved the first ever dual-frequency, multi-constellation GNSS-R observations over boreal forests and lakes using GPS, GLONASS and Galileo signals. 7) The first-ever dual-frequency multi-constellation GNSS-R dual-polarization measurements over boreal forests and lakes were obtained from the stratosphere during the BEXUS 19 using the PYCARO reflectometer operated in closed-loop mode.Global Navigation Satellite Systems Reflectometry (GNSS-R) es una técnica de radar multi-estático que usa señales de radio-navegación como señales de oportunidad. Esta técnica proporciona "wide-swath" y un mejor sampleado espacio-temporal en comparación con las misiones espaciales actuales. La falta de datos desde el espacio proporcionando señales de múltiples constelaciones (GPS, GLONASS, Galileo, Beidou) en doble banda (L1 y L2) y en doble polarización (RHCP y LHCP) sobre océano, tierra y criosfera continua siendo un problema por solucionar. 3Cat-2 es un cubesat de 6 unidades con el objetivo de explorar elementos fundamentales para mejorar el conocimiento sobre el scattering bi-estático sobre diferentes medios dispersores. Dado que la geolocalización de puntos de reflexión específicos está determinada solo por geometría, es necesario un requisito moderado de apuntamiento para corregir el diagrama de antena en aplicaciones de dispersometría. El lanzamiento del 3Cat-2 será en Q2 2016 en una órbitra heliosíncrona usando un cohete Long March II D. Esta tesis representa las contribuciones principales al desarrollo del satélite 3Cat2 para realizar observación de la tierra con GNSS-R incluyendo una nueva técnica: "the reconstructed-code GNSS-R". El diseño, desarrollo de la plataforma y un número de experimentos en tierra, desde avión y desde globo estratosférico para validar la técnica y optimizar el instrumento han sido realizados. En particular, las contribuciones de esta Ph.D. son: 1) un novedoso Global Navigation Satellite Systems Reflectometer que usa las señales P(Y) y C/A después de ser dispersadas sobre la superficie del mar para realizar medidas altimétricas muy precisas. (PYCARO). 2) La primera prueba de concepto de PYCARO se hizo en dos experimentos sobre un pantano y sobre el mar bajo diferentes condiciones de rugosidad. 3) La disperión de las señales GNSS sobre una superfice de agua ha sido estudiada para bajas altitudes para aplicaciones GNSS-R altimétricas de costa. La determinación precisa del nivel local del mar y el estado de las olas desde la costa puede proporcionar información útil de altimetría e información de olas. Para hacer un test de este concepto un experimento en el Canal d'Investigació i Experimentació Marítima (CIEM) fue realizado para dos estados sintéticos de rugosidad. 4) Dos experimentos en avión con esponsor de la ESA se realizaron para estudiar la preción y la exactitud relativa de cGNSS-R. 5) Los resultados empíricos del experimento GNSS-R en BEXUS 17 con esponsor de la ESA realizado en el norte de Suecia sobre bosques boreales mostró que la potencia reflejada de las señales es independiente de la altitud de la plataforma para un tiempo de integración coherente muy alto. 6) Una versión mejorada del PYCARO fue testeada en octubre del 2014 por segunda vez durante el BEXUS 19 que también fue patrocidado por la ESA. Este trabajo proporcionó las primeras medidas GNSS-R sobre bosques boreales en doble frecuencia usando varias constelaciones GNSS. 7) Las primeras medidas polarimétricas (RHCP y LHCP) de GNSS-R sobre bosques boreales también fueron conseguidas durante el experimento BEXUS 19.Award-winningPostprint (published version

Python software to transform GPS SNR wave phases to volumetric water content

[EN] The global navigation satellite system interferometric reflectometry is often used to extract information about the environment surrounding the antenna. One of the most important applications is soil moisture monitoring. This manuscript presents the main ideas and implementation decisions needed to write the Python code to transform the derived phase of the interferometric GPS waves, obtained from signal-to-noise ratio data continuously observed during a period of several weeks (or months), to volumetric water content. The main goal of the manuscript is to share the software with the scientific community to help users in the GPS-IR computation.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.Martín Furones, ÁE.; Anquela Julián, AB.; Ibañez Asensio, S.; Baixauli Soria, C.; Blanc Clavero, S. (2022). Python software to transform GPS SNR wave phases to volumetric water content. GPS Solutions. 26(1):1-5. https://doi.org/10.1007/s10291-021-01190-315261Chen Q, Won D, Akos DM, Small EE (2016) Vegetation using GPS interferometric reflectometry: experimental results with a horizontal polarized antenna. IEEE J Sel Top Appl Earth Obs Remote Sens 9(10):4771–4780Chew CC, Small EE, Larson KM, Zavorotny VU (2014) Effects of near-surface soil moisture on GPS SNR data: development and retrieval algorithm for soil moisture. IEEE T Geosci Remote Sens 52(1):537–543Chew CC, Small EE, Larson KM, Zavorotny UZ (2015) Vegetation sensing using GPS-interferometric reflectometry: theoretical effects of canopy parameters on signal-to-noise ratio data. IEEE Trans Geosci Remote Sens 53(5):2755–2764Chew CC, Small EE, Larson KM (2016) An algorithm for soil moisture estimation using GPS-interferometric reflectometry for bare and vegetated soil. GPS Solut 20(3):525–537Larson KM, Nievinski FG (2013) GPS snow sensing: results from the earthscope plate boundary observatory. GPS Solut 17(1):41–52Larson KM, Small EE (2015) PBO H2O data portal: documentation and derived data products. https://www.unavco.org/data/gps-gnss/derived-products/pbo-h2o/documentation/documentation.html#soil. Accessed Dec 2019Larson KM, Small EE, Gutmann ED, Bilich AL, Axelrad A, Braun JJ (2008a) Using GPS multipath to measure soil moisture fluctuations: initial results. GPS Solut 12(3):173–177Larson KM, Small EE, Gutmann ED, Bilich AL, Braun JJ, Zavorotny VU (2008b) Use of GPS receivers as a soil moisture network for water cycle studies. Geophys Res Lett 35:L24405. https://doi.org/10.1029/2008GL036013Larson KM, Braun JJ, Small EE, Zavorotny VU (2010) GPS multipath and its relation to near-surface soil moisture content. IEEE J Sel Top Appl Earth Obs Remote Sens 3(1):91–99Martín A, Ibañez S, Baixauli C, Blanc S, Anquela AB (2020a) Multi-constellation interferometric reflectometry with mass-market sensors as a solution for soil moisture monitoring. Hydrol Earth Syst Sci. https://doi.org/10.5194/hess-24-3573-2020Martín A, Luján R, Anquela AB (2020b) Python software tools for GNSS interferometric reflectometry (GNSS-IR). GPS Solut 24:94. https://doi.org/10.1007/s10291-020-01010-0Nievinski GG, Larson KM (2014) An open source GPS multipath simulator in Matlab/Octave. GPS Solut 18:473–481. https://doi.org/10.1007/s10291-014-0370-zRoesler C, Larson KM (2018) Software tools for GNSS interferometric reflectometry (GNSS-IR). GPS Solut. https://doi.org/10.1007/s10291-018-0744-8Roussel N, Frappart F, Ramillien G, Darroes J, Baup F, Lestarquit L, Ha MC (2016) Detection of soil moisture variations using GPS and GLONASS SNR data for elevation angles ranging from 2 to 70°. IEEE J Sel Top Appl Earth Obs Remote Sens 9(10):4781–4794Small EE, Larson KM, Chew CC, Dong J, Ochsner TE (2016) Validation of GPS-IR soil moisture retrievals: comparison of different algorithms to remove vegetation effects. IEEE J Sel Top Appl Earth Obs Remote Sens 9(10):4759–4770Vey S, Güntner A, Wickert J, Blume T, Ramatschi M (2016) Long-term soil moisture dynamics derived from GNSS interferometric reflectometry: a case study for Sutherland, South Africa. GPS Solut 20:641–654. https://doi.org/10.1007/s10291-015-0474-0Wan W, Larson KM, Small EE, Chew CC, Braun JJ (2015) Using geodetic GPS receivers to measure vegetation water content. GPS Solut 19:237–248Zhang S, Roussel N, Boniface K, Ha MC, Frappart F, Darrozes J, Baup F, Calvet JC (2017) Use of reflected GNSS SNR data to retrieve either soil moisture or vegetation height from a wheat crop. Hydrol Earth Syst Sci 21:4767–478

Application de la réflectométrie GNSS à l'étude des redistributions des masses d'eau à la surface de la Terre

GNSS reflectometry (or GNSS-R) is an original and opportunistic remote sensing technique based on the analysis of the electromagnetic waves continuously emitted by GNSS positioning systems satellites (GPS, GLONASS, etc.) that are captured by an antenna after reflection on the Earth’s surface. These signals interact with the reflective surface and hence contain information about its properties. When they reach the antenna, the reflected waves interfere with those coming directly from the satellites. This interference is particularly visible in the signal-to-noise ratio (SNR) parameter recorded by conventional GNSS stations. It is thus possible to reverse the SNR time series to estimate the reflective surface characteristics. If the feasibility and usefulness of thismethod are well established, the implementation of this technique poses a number of issues. Namely the spatio-temporal accuracies and resolutions that can be achieved and thus what geophysical observables are accessible.The aim of my PhD research work is to provide some answers on this point, focusing on the methodological development and geophysical exploitation of the SNR measurements performed by conventional GNSS stations. I focused on the estimation of variations in the antenna height relative to the reflecting surface (altimetry) and on the soil moisture in continental areas. The SNR data inversion method that I propose has been successfully applied to determine local variations of: (1) the sea level near the Cordouan lighthouse (not far from Bordeaux, France) from March 3 to May 31, 2013, where the main tidal periods and waves have been clearly identified ; and (2) the soil moisture in an agricultural plot near Toulouse, France, from February 5 to March 15, 2014. My method eliminates some restrictions imposed in earlier work, where the velocity of the vertical variation of the reflective surface was assumed to be negligible. Furthermore, I developed a simulator that allowed me to assess the influence of several parameters (troposphere, satellite elevation angle, antenna height, local relief, etc.) on the path of the reflected waves and hence on the position of the reflection points. My work shows that GNSS-R is a powerful alternative and a significant complement to the current measurement techniques, establishing a link between the different temporal and spatial resolutions currently achieved by conventional tools (sensors, radar, scatterometer, etc.). This technique offers the major advantage of being based on already-developed and sustainable satellites networks, and can be applied to any GNSS geodetic station, including permanent networks (e.g., the French RGP). Therefore, by installing a processing chain of these SNR acquisitions, data from hundreds of pre-existing stations could be used to make local altimetry measurements in coastal areas or to estimate soil moisture for inland antennas.La réflectométrie GNSS (ou GNSS-R) est une technique de télédétection originale et pportuniste qui consiste à analyser les ondes électromagnétiques émises en continu par la soixantaine de satellites des systèmes de positionnement GNSS (GPS, GLONASS, etc.), qui sont captées par une antenne après réflexion sur la surface terrestre. Ces signaux interagissent avec la surface réfléchissante et contiennent donc des informations sur ses propriétés. Au niveau de l’antenne, les ondes réfléchies interfèrent avec celles arrivant directement des satellites. Ces interférences sont particulièrement visibles dans le rapport signal-sur-bruit (SNR, i.e., Signal-to-Noise Ratio), paramètre enregistré par une station GNSS classique. Il est ainsi possible d’inverser les séries temporelles du SNR pour estimer des caractéristiques du milieu réfléchissant. Si la faisabilité et l’intérêt de cette méthode ne sont plus à démontrer, la mise en oeuvre de cette technique pose un certain nombre de problèmes, à savoir quelles précisions et résolutions spatio-temporelles peuvent être atteintes, et par conséquent, quels sont les observables géophysiques accessibles.Mon travail de thèse a pour objectif d’apporter des éléments de réponse sur ce point, et est axé sur le développement méthodologique et l’exploitation géophysique des mesures de SNR réalisées par des stations GNSS classiques.Je me suis focalisé sur l’estimation des variations de hauteur de l’antenne par rapport à la surfaceréfléchissante (altimétrie) et de l’humidité du sol en domaine continental. La méthode d’inversion des mesures SNR que je propose a été appliquée avec succès pour déterminer les variations locales de : (1) la hauteur de la mer au voisinage du phare de Cordouan du 3 mars au 31 mai 2013 où les ondes de marées et la houle ont pu être parfaitement identifiées ; et (2) l’humidité du sol dans un champ agricole à proximité de Toulouse, du 5 février au 15 mars 2014. Ma méthode permet de s’affranchir de certaines restrictions imposées jusqu’à présent dans les travaux antérieurs, où la vitesse de variation verticale de la surface de réflexion était supposée négligeable. De plus, j’ai développé un simulateur qui m’a permis de tester l’influence de nombreux paramètres (troposphère, angle d’élévation du satellite, hauteur d’antenne, relief local, etc.) sur la trajectoire des ondes réfléchies et donc sur la position des points de réflexion. Mon travail de thèse montre que le GNSS-R est une alternative performante et un complément non négligeable aux techniques de mesure actuelles, en faisant le lien entre les différentes résolutions temporelles et spatiales actuellement atteintes par les outils classiques (sondes, radar, diffusiomètres, etc.). Cette technique offre l’avantage majeur d’être basé sur un réseau de satellites déjà en place et pérenne, et est applicable à n’importe quelle station GNSS géodésique, notamment celles des réseaux permanents (e.g., le RGP français). Ainsi, en installant une chaîne de traitement de ces acquisitions de SNR en domaine côtier, il serait possible d’utiliser les mesures continues des centaines de stations pré-existantes, et d’envisager de réaliser des mesures altimétriques à l’échelle locale, ou de mesurer l’humidité du sol pour les antennes situées à l’intérieur des terres

Wind direction signatures in GNSS-R observables from space

Peer ReviewedPostprint (published version

GNSS Reflectometry for land surface monitoring and buried object detection

Global Navigation Satellite System Reflectometry (GNSS-R) is attracting growing interest nowadays for several remote sensing applications. As a bistatic radar, the transmitter and the receiver are not co-located and in the special case of GNSS-R, the GNSS satellites are acting as transmitters and the receiver can be mounted either in a static position or onboard a aircraft or low orbit satellite. Various information about the surface from where the GNSS signals are reflected or scattered can be extracted by means of reflected signal strength, code delay, carrier phase delay, interference with direct GNSS signals and so on. Possible applications cover soil moisture retrieval, ice topography and thickness detection, snow depth estimation, vegetation coverage, sea state monitoring such as sea wind and surface roughness, sea salinity… In this work, soil moisture retrieval was mostly focused on. Hardware including antennas and receivers was studied and designed. Our first strategy of soil moisture retrieval is to apply a single Left Hand Circular Polarization (LHCP) antenna for reflected signal reception. Therefore multiple types of antennas such as the helix antenna, the patch antenna and several commercial antennas were designed, simulated or tested in the anechoic chamber. Two receiver solutions were used in our group and both of them apply the SiGe GPS frontend. The first solution is a PC based one: the collection and store of the raw incoming reflected GPS signals were done by the NGrab software (designed by NAVSAS Group of Politecnico di Torino) installed in a standard PC. The other solution was developed in our group and it is operated by a single Hackberry board, which consists of power supply, storage subsystem and customized Linux Debian operating system. The light weight and small size enable this compact receiver to perform flight measurement onboard UAVs. Both of the above mentioned receivers only store raw sampled data and no real time signal processing is performed on board. Post processing is done by Matlab program which makes correlations in both time and frequency domain with incoming signals using the local generated GPS C/A code replica. The so-called Delay Doppler Map (DDM) is therefore generated through this correlation. Signal to Noise Ratio (SNR) can be calculated through Delay Waveform (DW) which is extracted from DDM at the Doppler frequency where the correlation peak exists. Received signal power can be obtained knowing the noise power which is given in a standard equation. In order to better plan a static measurement and to georeference specular points on the surface, programs for georeferencing specular points on either Google Maps or an x-y plane centered at the receiver position were developed. Fly dynamics in terms of roll, pitch and yaw influencing the antenna gain due to the variation of incident angles were also studied in order to compensate the gain to the received signal. Two soil moisture retrieval algorithms were derived corresponding to two receiving schemes. The first one is for the receiving of only LHCP reflected signals. In this case, the surface is assumed to be perfectly smooth and the received signal is seen to consist of only coherent component caused by specular reflection. Dielectric constant can be retrieved from the processed SNR. Two measurement campaigns were carried out using this single LHCP system. The first campaign is a flight measurement overflown a big portion of rice fields when most of the fields were flooded. It was a test measurement on the SNR sensitivity to water/no-water surfaces and an attempt of dielectric constant retrieval was also performed. SNR showed good sensitivity to the surface water content and dielectric constant was also checked to be reasonable. The second campaign is in static positions and it includes two experiments. This campaign initially aimed at testing the sensitivity of the compact receiver to different surface moisture. Results of both SNR and retrieved dielectric constant showed to be coherent with the surface moisture changes. The other retrieval algorithm is for the receiving of both LHCP and RHCP reflected signals concurrently. The cross polarization power ratio (LHCP/RHCP) is believed to be independent of surface roughness by several previous studies and this idea was also verified during the deriving process for either specular reflection case (only coherent component) or diffuse scattering condition (incoherent component). For diffuse scattering, three well known models were applied which are the Kirchhoff Approximation in stationary-phase approximation (Kirchhoff Geometrical Optics, KGO), Kirchhoff Approximation in Physical Optics Approximation (KPO) and Small Perturbation Method (SPM). These three models cover different roughness surfaces from very rough (KGO) to slightly rough surfaces (SPM). All the derived results of cross polarization ratio for the three models were verified to be independent of surface properties and depend on only dielectric constant of soil and incident angle. A new application of GNSS-R technique for the possibility of detection of buried objects was firstly investigated by our group. It has the potential use for man-made mines detection in the military field. Two measurement campaigns were carried out and the variation of the SNR level due to the presence of a metallic object was investigated. The first measurement campaign was performed in a static condition on a sandy terrain to check the functionality of the system. And the presence of the metallic object was detected also in the case of wet terrain. In the second measurement campaign, the antenna was moving along a given path and the possibility of detecting the object dimensions was highlighted. The results show the possibility of adopting this technique on board a remotely controlled UAV for metal object and even its dimension detection. A measurement of snow depth attempting to relate it to reflected LHCP SNR is briefly presented and discussed in Chapter 7

Sea level measurement using single GNSS antenna SNR signals

This thesis presents a possible method to calculate sea level variation using geodetic-quality Global Navigate Satellite System (GNSS) receivers. Three antennas are used: two small antennas and a choke ring one, analyzing only Global Positioning System signals. The main goal of the thesis is to test a modified configuration for antenna set up. In particular, measurements obtained tilting one antenna to face the horizon are compared to measurements obtained from antennas looking upward. The location of the experiment is a coastal environment nearby the Onsala Space Observatory in Sweden. Sea level variations are obtained using periodogram analysis of the SNR signal and compared to synthetic gauge generated from two independent tide gauges. The choke ring antenna provides poor result, with an RMS around 6 cm and a correlation coefficients of 0.89. The smaller antennas provide correlation coefficients around 0.93. The antenna pointing upward present an RMS of 4.3 cm and the one pointing the horizon an RMS of 6.7 cm. Notable variation in the statistical parameters is found when modifying the length of the interval analyzed. In particular, doubts are risen on the reliability of certain scattered data. No relation is found between the accuracy of the method and weather conditions. Possible methods to enhance the available data are investigated, and correlation coefficient above 0.97 can be obtained with small antennas when sacrificing data points. Hence, the results provide evidence of the suitability of SNR signal analysis for sea level variation in coastal environment even in the case of adverse weather conditions. In particular, tilted configurations provides comparable result with upward looking geodetic antennas. A SNR signal simulator is also tested to investigate its performance and usability. Various configuration are analyzed in combination with the periodogram procedure used to calculate the height of reflectors. Consistency between the data calculated and those received is found, and the overall accuracy of the height calculation program is found to be around 5 mm for input height below 5 m. The procedure is thus found to be suitable to analyze the data provided by the GNSS antennas at Onsala

Carrier multipath mitigation in linear combinations of Global Navigation Satellite Systems measurements

Global Navigation Satellite Systems (GNSS) are the main systems that provide positioning, navigation and timing at a global level. They are being used in numerous applications in different sectors including transport, military, oil & gas, agriculture as well as location based services. A significant number of these applications require centimetre-level positioning accuracy, a challenging feat due to the many error sources that affect GNSS measurements. These include errors at the satellite, propagation medium, and receiver levels. Most of these errors can be mitigated by modeling, or by exploiting their spatial and temporal correlation characteristics. However, multipath errors, which result from the combination of the direct signal with reflected signals in the vicinity of the receiver antenna, are difficult to model and therefore, difficult to mitigate. Furthermore, high accuracy positioning applications typically rely on linear combinations of measurements at different frequencies (e.g. L1 and L2 in the case of the Global Positioning System) to mitigate frequency-dependent errors such as ionospheric errors (i.e. ionosphere free combination) or otherwise facilitate position calculation (e.g. Wide Lane observable). The multipath errors associated with such combinations are significantly larger than those of individual signals. The dependency of the multipath error on the environment and its low level in single frequency measurements (i.e. up to quarter of wavelength) makes modelling and mitigating it very difficult. Current techniques attempt to mitigate multipath errors for measurements at each individual frequency, independently of the error at other frequencies, even when linear combinations of measurements are used. The literature review carried out in this thesis has drawn three main conclusions regarding carrier multipath mitigation. Firstly, existing carrier multipath mitigation techniques are inaccurate, impractical or not effective. Secondly most of the practical techniques attempt to mitigate the error by de-weighting the measurements which are most prone to the multipath error (i.e measurement at low elevation). Thirdly, existing weighting techniques are oversimplified and do not reflect the error level accurately. In this research and for the first time, carrier multipath errors have been studied directly at the linear combination level. This is by exploiting the dispersive nature of multipath errors in order to model and correct them. New carrier multipath mitigation techniques applicable to linear combinations of measurements have been developed in this thesis on the basis of a new error model and a new observable referred to as the IFM (Inter-Frequency carrier Multipath). The IFM is computed from carrier phase measurements at two different frequencies, and corresponds to the combined multipath errors of those signals. In addition to multipath mitigation, this observable has various other applications. The well-defined relationship between the IFM and carrier multipath errors is used in this thesis to develop multipath mitigation techniques based on two approaches: multipath correction and measurement weighting. The new mitigation techniques are applicable to linear combinations of observations such as Wide Lane (WL) and Ionosphere Free (IF) carrier phase measurements in double differenced mode. The new multipath mitigation techniques have been validated using real data and the results compared with those obtained using the elevation weighting technique. The results show that the new methods developed in this thesis improve the mean error of horizontal position by up to 33% when using the IF combination. The results also show improvements of up to 78% in the time it takes to resolve ambiguities when using the WL combination.Open Acces

Use of reflected GNSS SNR data to retrieve either soil moisture or vegetation height from a wheat crop

This work aims to estimate soil moisture and vegetation height from Global Navigation Satellite System (GNSS) Signal to Noise Ratio (SNR) data using direct and reflected signals by the land surface surrounding a ground-based antenna. Observations are collected from a rainfed wheat field in southwestern France. Surface soil moisture is retrieved based on SNR phases estimated by the Least Square Estimation method, assuming the relative antenna height is constant. It is found that vegetation growth breaks up the constant relative antenna height assumption. A vegetation-height retrieval algorithm is proposed using the SNR-dominant period (the peak period in the average power spectrum derived from a wavelet analysis of SNR). Soil moisture and vegetation height are retrieved at different time periods (before and after vegetation's significant growth in March). The retrievals are compared with two independent reference data sets: in situ observations of soil moisture and vegetation height, and numerical simulations of soil moisture, vegetation height and above-ground dry biomass from the ISBA (interactions between soil, biosphere and atmosphere) land surface model. Results show that changes in soil moisture mainly affect the multipath phase of the SNR data (assuming the relative antenna height is constant) with little change in the dominant period of the SNR data, whereas changes in vegetation height are more likely to modulate the SNR-dominant period. Surface volumetric soil moisture can be estimated (R2  =  0.74, RMSE  =  0.009 m3 m−3) when the wheat is smaller than one wavelength (∼ 19 cm). The quality of the estimates markedly decreases when the vegetation height increases. This is because the reflected GNSS signal is less affected by the soil. When vegetation replaces soil as the dominant reflecting surface, a wavelet analysis provides an accurate estimation of the wheat crop height (R2  =  0.98, RMSE  =  6.2 cm). The latter correlates with modeled above-ground dry biomass of the wheat from stem elongation to ripening. It is found that the vegetation height retrievals are sensitive to changes in plant height of at least one wavelength. A simple smoothing of the retrieved plant height allows an excellent matching to in situ observations, and to modeled above-ground dry biomass