Learning-based NLOS Detection and Uncertainty Prediction of GNSS Observations with Transformer-Enhanced LSTM Network

The global navigation satellite systems (GNSS) play a vital role in transport systems for accurate and consistent vehicle localization. However, GNSS observations can be distorted due to multipath effects and non-line-of-sight (NLOS) receptions in challenging environments such as urban canyons. In such cases, traditional methods to classify and exclude faulty GNSS observations may fail, leading to unreliable state estimation and unsafe system operations. This work proposes a Deep-Learning-based method to detect NLOS receptions and predict GNSS pseudorange errors by analyzing GNSS observations as a spatio-temporal modeling problem. Compared to previous works, we construct a transformer-like attention mechanism to enhance the long short-term memory (LSTM) networks, improving model performance and generalization. For the training and evaluation of the proposed network, we used labeled datasets from the cities of Hong Kong and Aachen. We also introduce a dataset generation process to label the GNSS observations using lidar maps. In experimental studies, we compare the proposed network with a deep-learning-based model and classical machine-learning models. Furthermore, we conduct ablation studies of our network components and integrate the NLOS detection with data out-of-distribution in a state estimator. As a result, our network presents improved precision and recall ratios compared to other models. Additionally, we show that the proposed method avoids trajectory divergence in real-world vehicle localization by classifying and excluding NLOS observations.Comment: Accepted for the IEEE ITSC202

Kinematic GNSS tropospheric estimation and mitigation over a range of altitudes

PhD ThesisThis thesis investigates the potential for estimating tropospheric delay from Global Navigation Satellite Systems (GNSS) stations on moving platforms experiencing a change in altitude. The ability to accurately estimate tropospheric delay in kinematic GNSS positioning has implications for improved height accuracy due to the mitigation of a major GNSS error source, and for the collection of atmospheric water vapour data for meteorology and climate studies. The potential for extending current kinematic GNSS positioning estimates of tropospheric delay from sea level based studies to airborne experiments, and the achievable height accuracy from a range of tropospheric mitigation strategies used in airborne GNSS positioning, are explored. An experiment was established at the Snowdon Mountain Railway (SMR), utilising the railway to collect a repeatable kinematic dataset, profiling 950 m of the lower atmosphere over a 50 day period. GNSS stations on stable platforms and meteorological sensors were installed at the extremities of the trajectory, allowing reference tropospheric delays and coordinates to be established. The retrieval of zenith wet delay (ZWD) from kinematic GNSS solutions using tropospheric estimation strategies is validated against an interpolated reference ZWD between GNSS stations on stable platforms, together with profiles from 100 m resolution runs of the UK Met Office Unified Model. Agreement between reference ZWD values and a combined GPS+GLONASS precise point positioning (PPP) solution is demonstrated with an accuracy of 11.6 mm (RMS), similar to a relative positioning solution and previous shipborne studies. The impact on the height accuracy from estimating tropospheric delay in kinematic GNSS positioning is examined by comparing absolute and relative GNSS positioning solutions to a reference trajectory generated from a relative GNSS positioning solution ii processed with reference to the GNSS stations on stable platforms situated at the extremities of the SMR. A height accuracy with a standard deviation of 72 mm was demonstrated for the GPS+GLONASS PPP solution, similar to a GPS-only relative solution, and providing an improvement over the GPS-only PPP solution.UK Natural Environment Research Council (NERC) studentship, and part of the work was funded by the Royal Institution of Chartered Surveyors (RICS) Education Trust

Data driven joint sensor fusion and regression based on geometric mean squared error

This paper explores the problem of estimating a temporal series measured from multiple independent sensors with unequal and stationary measurement errors with unknown variances. By formulating the data fusion problem as a joint Maximum Likelihood estimation of sensor covariances and a fusion rule, a batch data driven method is derived involving a residual covariance determinant minimization of a diagonal matrix. It is shown that yielding useful learning from data with good generalization properties in the joint regression and fusion approach requires the assumption of some structure on the sensor noises and/or on the temporal series to be estimated. An efficient data driven algorithm is proposed to obtain the best linear sensor combiner, whose performance is numerically analyzed and compared with the Cramer-Rao Lower Bound of the estimated parameters.This work has been supported by the Spanish Ministry of Science and Innovation through project RODIN (PID2019-105717RB-C22 / AEI / 10.13039/501100011033) and by the Catalan Government (AGAUR) under grant 2017 SGR 578.Peer ReviewedPostprint (author's final draft

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

GNSS-based global ionospheric maps : real-time combination, time resolution and applications on space weather monitoring

Tesi amb una secció retallada per drets d'editor.The research of this paper-based dissertation is focused on the Global Ionospheric Maps (GIMs) based on Global Navigation Satellite System (GNSS) including real-time combination, validation, time resolution and applications. The novelty of these works can be summarized as follows: The first contribution is to connect GIM assessment methods in post-processing and real-time mode including Jason-altimeter Vertical Total Electron Content (VTEC) assessment, GNSS differences of Slant Total Electron Content (dSTEC) assessment and real-time dSTEC (RT-dSTEC) assessment. With the RT-dSTEC assessment, we can assess the accuracy and calculate the weight of different real-time GIMs for combination in real-time mode. The Jason-altimeter VTEC assessment and dSTEC assessment can be used for evaluating GIMs over oceans and continental regions, respectively. In addition, the accurate GIMs shown in the GIM assessment methods can be regarded as reliable representations of global VTEC. The second contribution is to apply the RT-dSTEC assessment in real-time mode for the combination of different International GNSS Service (IGS) real-time GIMs. The IGS combined real-time GIM is generated to provide robust ionospheric corrections for real-time GNSS positioning and reliable global VTEC distribution for earth observations. The current status of IGS real-time GIMs from different centers is summarized and compared. The Jason-altimeter VTEC assessment and dSTEC assessment in post-processing mode are used for the validation of IGS real-time GIMs. The sensibility of real-time weighting technique by RT-dSTEC assessment is also verified. The third contribution is to investigate the influence of temporal resolution on the performance of GIMs. The variation of ionosphere is typically assumed as linear between two consecutive GIM TEC maps in a sun-fixed reference frame for up to few hours. However, the variation of ionospheric TEC is irregular due to the occurrence of space weather events. One and a half solar cycle of the IGS GIM with higher time resolution and accuracy (the UPC-IonSAT Quarter-of-an-hour time resolution Rapid GIM, UQRG) has been taken as a baseline to downsample them to all possible sub-daily temporal resolutions. The performance of the resulting GIMs has been evaluated taking into account the geographical position, solar and geomagnetic activity by Jason-altimeter VTEC assessment and dSTEC assessment. The fourth contribution is to propose a new way of estimating the spatial and temporal components of the VTEC gradient. The determination of ionospheric perturbation degrees can be helpful for guaranteeing the safety level of Satellite-Based Augmentation System (SBAS) and Ground-Based Augmentation System (GBAS) services. In order to estimate the spatial and temporal components of the VTEC gradient on a global scale, the accurate UQRG is selected. The VTEC gradient indices derived from UQRG GIMs (VgUG) allow users to obtain full (non-relative) values of TEC spatial gradients and temporal variations separately. The Regional VTEC spatial Gradient indices, based on UQRG (RVGU) and the Regional Ionospheric Disturbance index based on UQRG (RIDU), are proposed to estimate the regional ionospheric perturbation degree over selected regions. In addition, the spatial and temporal components of VTEC gradient at grid points of UQRG on a global scale are also introduced. The fifth contribution is to define a new ionospheric storm scale. The ionospheric response to high geomagnetic activity, ionospheric storm, can enlarge GNSS positioning errors by the increase of ionospheric electron density and disable high-frequency communications by the decrease of ionospheric electron density. To characterize the ionospheric state on a global scale, reliable global VTEC distribution is essential. According to previous studies, UQRG is one of the most accurate GIM. In this regard, the new Ionospheric storm Scale based on UQRG, IsUG, is proposed.La investigación de esta tesis doctoral se centra en los Mapas Ionosféricos Globales (GIMs) basados en el Sistema Global de Navegación por Satélite (GNSS), incluyendo la combinación en tiempo real, la validación, la resolución temporal y su aplicación. La novedad de los trabajos presentados puede resumirse como sigue: La primera contribución consiste en conectar los métodos de evaluación de los GIM en modo de posprocesamiento y en tiempo real, incluyendo la evaluación VTEC gracias a las medidas de los altímetros Jason, la evaluación del contenido total de electrones diferencial (dSTEC) y la evaluación dSTEC en tiempo real (RT-dSTEC). Con la evaluación RT-dSTEC, podemos evaluar la precisión y calcular el peso de diferentes GIM en tiempo real para su combinación también en tiempo real. La evaluación VTEC del altímetro Jason y la evaluación dSTEC pueden utilizarse para evaluar los GIM sobre los océanos y las regiones continentales, respectivamente. Además, los GIM precisos mostrados en los métodos de evaluación de GIM pueden considerarse como representaciones fiables del contenido total de electrones vertical global (VTEC). La segunda contribución consiste en aplicar la evaluación RT-dSTEC en tiempo real para la combinación de diferentes GIM del Servicio Internacional GNSS (IGS), todo ello en tiempo real. El GIM IGS combinado resultante proporciona correcciones ionosféricas robustas para el posicionamiento GNSS en tiempo real y una distribución global de VTEC fiable para las observaciones terrestres. Se resume y compara el estado actual de los GIM en tiempo real de diferentes centros IGS. La evaluación de VTEC respecto de los altímetros Jason y la evaluación de dSTEC en modo de posprocesamiento también se utilizan para la validación de los GIM en tiempo real del IGS. Y se verifica la sensibilidad de la técnica de ponderación en tiempo real mediante la evaluación RT-dSTEC. La tercera contribución consiste en proponer una nueva forma de estimar las componentes espaciales y temporales del gradiente VTEC. La determinación de los grados de perturbación ionosférica puede ser útil para garantizar el nivel de seguridad de los servicios del Sistema de Aumento Basado en Satélites (SBAS) y del Sistema de Aumento Basado en Tierra (GBAS). Para estimar los componentes espaciales y temporales del gradiente de VTEC a escala global, se selecciona el GIM UQRG debido a su exactitud y resolución temporal. Los índices de gradiente VTEC derivados de los GIM de UQRG (VgUG) permiten a los usuarios obtener valores completos (no relativos) de gradientes espaciales de VTEC y de las variaciones temporales por separado. Los índices de gradiente espacial VTEC regional, basados en UQRG (RVGU) y el índice de perturbación ionosférica regional basado en UQRG (RIDU), se proponen para estimar el grado de perturbación ionosférica regional sobre zonas de interés. Además también se introducen los componentes espaciales y temporales del gradiente VTEC en los puntos de la cuadrícula con valores proporcionados por UQRG a escala global. La cuarta contribución consiste en definir una nueva escala de tormentas ionosféricas. La respuesta ionosférica a la alta actividad geomagnética, la tormenta ionosférica, puede aumentar los errores de posicionamiento del GNSS por el aumento de la densidad de electrones ionosféricos e inhabilitar las comunicaciones de alta frecuencia por la disminución y en general rápida variación de la densidad de electrones ionosféricos. Para caracterizar el estado de la ionosfera a escala global, es esencial contar con una distribución global fiable de VTEC. Según estudios anteriores, el UQRG es uno de los GIM más precisos. En este sentido se propone la nueva Escala de tormentas ionosféricas basada en UQRG, IsUG.Postprint (published version

Precise Point Positioning Augmentation for Various Grades of Global Navigation Satellite System Hardware

The next generation of low-cost, dual-frequency, multi-constellation GNSS receivers, boards, chips and antennas are now quickly entering the market, offering to disrupt portions of the precise GNSS positioning industry with much lower cost hardware and promising to provide precise positioning to a wide range of consumers. The presented work provides a timely, novel and thorough investigation into the positioning performance promise. A systematic and rigorous set of experiments has been carried-out, collecting measurements from a wide array of low-cost, dual-frequency, multi-constellation GNSS boards, chips and antennas introduced in late 2018 and early 2019. These sensors range from dual-frequency, multi-constellation chips in smartphones to stand-alone chips and boards. In order to be comprehensive and realistic, these experiments were conducted in a number of static and kinematic benign, typical, suburban and urban environments. In terms of processing raw measurements from these sensors, the Precise Point Positioning (PPP) GNSS measurement processing mode was used. PPP has become the defacto GNSS positioning and navigation technique for scientific and engineering applications that require dm- to cm-level positioning in remote areas with few obstructions and provides for very efficient worldwide, wide-array augmentation corrections. To enhance solution accuracy, novel contributions were made through atmospheric constraints and the use of dual- and triple-frequency measurements to significantly reduce PPP convergence period. Applying PPP correction augmentations to smartphones and recently released low-cost equipment, novel analyses were made with significantly improved solution accuracy. Significant customization to the York-PPP GNSS measurement processing engine was necessary, especially in the quality control and residual analysis functions, in order to successfully process these datasets. Results for new smartphone sensors show positioning performance is typically at the few dm-level with a convergence period of approximately 40 minutes, which is 1 to 2 orders of magnitude better than standard point positioning. The GNSS chips and boards combined with higher-quality antennas produce positioning performance approaching geodetic quality. Under ideal conditions, carrier-phase ambiguities are resolvable. The results presented show a novel perspective and are very promising for the use of PPP (as well as RTK) in next-generation GNSS sensors for various application in smartphones, autonomous vehicles, Internet of things (IoT), etc

Geodetic Sciences

Space geodetic techniques, e.g., global navigation satellite systems (GNSS), Very Long Baseline Interferometry (VLBI), satellite gravimetry and altimetry, and GNSS Reflectometry & Radio Occultation, are capable of measuring small changes of the Earth�s shape, rotation, and gravity field, as well as mass changes in the Earth system with an unprecedented accuracy. This book is devoted to presenting recent results and development in space geodetic techniques and sciences, including GNSS, VLBI, gravimetry, geoid, geodetic atmosphere, geodetic geophysics and geodetic mass transport associated with the ocean, hydrology, cryosphere and solid-Earth. This book provides a good reference for geodetic techniques, engineers, scientists as well as user community