ML estimator and hybrid beamformer for multipath and interference mitigation in GNSS receivers

This paper addresses the estimation of the code-phase(pseudorange) and the carrier-phase of the direct signal received from a direct-sequence spread-spectrum satellite transmitter. The signal is received by an antenna array in a scenario with interference and multipath propagation. These two effects are generally the limiting error sources in most high-precision positioning applications. A new estimator of the code- and carrier-phases is derived by using a simplified signal model and the maximum likelihood (ML) principle. The simplified model consists essentially of gathering all signals, except for the direct one, in a component with unknown spatial correlation. The estimator exploits the knowledge of the direction-of-arrival of the direct signal and is much simpler than other estimators derived under more detailed signal models. Moreover, we present an iterative algorithm, that is adequate for a practical implementation and explores an interesting link between the ML estimator and a hybrid beamformer. The mean squared error and bias of the new estimator are computed for a number of scenarios and compared with those of other methods. The presented estimator and the hybrid beamforming outperform the existing techniques of comparable complexity and attains, in many situations, the Cramér–Rao lower bound of the problem at hand.Peer Reviewe

Time–frequency analysis of the Galileo satellite clocks: looking for the J2 relativistic effect and other periodic variations

When observed from the ground, the frequency of the atomic clocks flying on the satellites of a Global Navigation Satellite System is referred to as apparent frequency, because it is observed through the on-board signal generation chain, the propagation path, the relativistic effects, the measurement system, and the clock estimation algorithm. As a consequence, the apparent clock frequency is affected by periodic variations of different origins such as, for example, the periodic component of the J2 relativistic effect, due to the oblateness of the earth, and the clock estimation errors induced by the orbital estimation errors. We present a detailed characterization of the periodic variations affecting the apparent frequency of the Galileo clocks, obtained by applying time–frequency analysis and other signal processing techniques on space clock data provided by the European Space Agency. In particular, we analyze one year of data from three Galileo Passive Hydrogen Masers, flying on two different orbital planes. Time–frequency analysis reveals how the spectral components of the apparent frequency change with time. For example, it confirms that the amplitude of the periodic signal due to the orbital estimation errors depends on the angle between the sun and the orbital plane. Moreover, it allows to find a more precise estimate of the amplitude of the J2 effect, in agreement with the prediction of the general theory of relativity, and it shows that such amplitude suddenly decreases when the corresponding relativistic correction is applied to the data, thus validating the analytical formula used for the correction

Time-frequency analysis of the Galileo satellite clocks: looking for the J2 relativistic effect and other periodic variations

When observed from the ground, the frequency of the atomic clocks flying on the satellites of a Global Navigation Satellite System is referred to as apparent frequency, because it is observed through the on-board signal generation chain, the propagation path, the relativistic effects, the measurement system, and the clock estimation algorithm. As a consequence, the apparent clock frequency is affected by periodic variations of different origins such as, for example, the periodic component of the J2 relativistic effect, due to the oblateness of the earth, and the clock estimation errors induced by the orbital estimation errors. We present a detailed characterization of the periodic variations affecting the apparent frequency of the Galileo clocks, obtained by applying time-frequency analysis and other signal processing techniques on space clock data provided by the European Space Agency. In particular, we analyze one year of data from three Galileo Passive Hydrogen Masers, flying on two different orbital planes. Time-frequency analysis reveals how the spectral components of the apparent frequency change with time. For example, it confirms that the amplitude of the periodic signal due to the orbital estimation errors depends on the angle between the sun and the orbital plane. Moreover, it allows to find a more precise estimate of the amplitude of the J2 effect, in agreement with the prediction of the general theory of relativity, and it shows that such amplitude suddenly decreases when the corresponding relativistic correction is applied to the data, thus validating the analytical formula used for the correction

Performance Assessment of GNSS Receiver Networks with Software Model Evaluation

This work details methods of evaluation for GNSS receiver networks using evaluation techniques implemented in software. Evaluation methods are formulated in this work that estimate the availability and validity rates of GPS receiver data within a GNSS receiver network. These methods are implemented as part of a new software suite developed to handle data from hundreds to thousands of GPS receivers effectively and efficiently. Details of the software suite design and implementation that are critical to the performance and effectiveness of handling large sets of receiver measurement data are detailed. The software and methods developed are applied to the CORS network by evaluating measurement data provided by 708 stations in the CORS network for one day. The rates of data availability and validity are reported, which are used to validate the effectiveness of the software. The results found show that the software is effective for analysis of the CORS network for a large number of GPS receivers

Context Detection for Advanced Self-Aware Navigation using Smartphone Sensors

Navigation and positioning systems dependent on both the operating environment and the behaviour of the host vehicle or user. The environment determines the type and quality of radio signals available for positioning and the behaviour can contribute additional information to the navigation solution. In order to operate across different contexts, a context-adaptive navigation solution introduces an element of self-awareness by detecting the operating context and configuring the positioning system accordingly. This paper presents the detection of both environmental and behavioural contexts as a whole, building the foundation of a context-adaptive navigation system. Behavioural contexts are classified using measurements from accelerometers, gyroscopes, magnetometers and the barometer by supervised machine learning algorithms, yielding an overall 95% classification accuracy. A connectivity dependent filter is then implemented to improve the behavioural detection results. Environmental contexts are detected from GNSS measurements. They are classified into indoor, intermediate and outdoor categories using a probabilistic support vector machine (SVM), followed by a hidden Markov model (HMM) used for time-domain filtering. As there will never be completely reliable context detection, the paper also shows how environment and behaviour association can contribute to reducing the chances of the context determination algorithms selecting an incorrect context. Finally, the proposed contextdetermination algorithms are tested in a series of multi-context scenarios

Analysis of ionospheric disruptions in GNSS signals from Tonga eruption

The Tonga volcano eruption at 04:15 UT on 2022-01-15 released enormous amounts of energy into the atmosphere, causing very significant geophysical variations not only in the immediate proximity of the epicenter but also globally across the whole atmosphere. The released energy generates perturbations on the electronic density present on the atmosphere, known as Traveling Ionospheric Disturbances (TIDs), i.e., wave-like propagating irregularities that alter the electron density environment and play an important role spreading radio signals propagating through the ionosphere. Geomagnetic and ionospheric phenomena affect communications, GNSS, and other systems on which our technological society depends. The present final master’s thesis aims to analyse some of the most relevant TIDs characteristics (such as propagation speed, time, etc.) as a function of the distance from the eruption in Global Navigation Satellite System (GNSS) signals. First, evaluate Receiver Independent Exchange Format (RINEX) files, i.e., a data interchange format for raw satellite navigation system data, and then, compute Prefit Residuals, i.e., the input data for the navigation equations. With this data, TIDs will be analysed with a series of indices that sample in post-process the disturbance of the ionosphere, developed by Research group of Astronomy and GEomatics of the Universitat Politecnica de Catalunya (gAGE).La erupción del volcán Tonga a las 04:15 UT del 15-01-2022 liberó enormes cantidades de energía a la atmósfera, desencadenando variaciones geofísicas muy significativas no solo en la proximidad inmediata del epicentro sino también a nivel mundial en toda la atmósfera. Estas variaciones se conocen como perturbaciones ionosféricas viajeras (TID, por sus si-glas en inglés), es decir, irregularidades de propagación en forma de onda que alteran el entorno de densidad de electrones y desempeñan un papel importante en la propagación de señales de radio que se propagan a través de la ionosfera. Los fenómenos geomagnéticos e ionosféricos afectan a las comunicaciones, GNSS y otros sistemas de los que depende nuestra sociedad tecnológica. La presente tesis final de máster tiene como objetivo analizar algunas de las características más relevantes de los TIDs (como la velocidad de propagación, el tiempo, etc.) en función de la distancia desde la erupción en las señales del Sistema Global de Navegación por Satélite (GNSS). Primero, evaluando los archivos de Receiver Independent Exchange Format (RINEX), es decir, un formato de intercambio de datos para los datos brutos del sistema de navegación por satélite, y luego, calculando los residuos de preajuste, es decir, los datos de entrada para las ecuaciones de navegación. Con estos datos, se analizarán las TIDs con una serie de índices que muestrean en postproceso la perturbación de la ionosfera, desarrollados por el grupo de investigación de Astronomía y GEomática de la Universitat Politecnica de Cata-lunya (gAGE).Incomin

GNSS-free outdoor localization techniques for resource-constrained IoT architectures : a literature review

Large-scale deployments of the Internet of Things (IoT) are adopted for performance improvement and cost reduction in several application domains. The four main IoT application domains covered throughout this article are smart cities, smart transportation, smart healthcare, and smart manufacturing. To increase IoT applicability, data generated by the IoT devices need to be time-stamped and spatially contextualized. LPWANs have become an attractive solution for outdoor localization and received significant attention from the research community due to low-power, low-cost, and long-range communication. In addition, its signals can be used for communication and localization simultaneously. There are different proposed localization methods to obtain the IoT relative location. Each category of these proposed methods has pros and cons that make them useful for specific IoT systems. Nevertheless, there are some limitations in proposed localization methods that need to be eliminated to meet the IoT ecosystem needs completely. This has motivated this work and provided the following contributions: (1) definition of the main requirements and limitations of outdoor localization techniques for the IoT ecosystem, (2) description of the most relevant GNSS-free outdoor localization methods with a focus on LPWAN technologies, (3) survey the most relevant methods used within the IoT ecosystem for improving GNSS-free localization accuracy, and (4) discussion covering the open challenges and future directions within the field. Some of the important open issues that have different requirements in different IoT systems include energy consumption, security and privacy, accuracy, and scalability. This paper provides an overview of research works that have been published between 2018 to July 2021 and made available through the Google Scholar database.5311-8814-F0ED | Sara Maria da Cruz Maia de Oliveira PaivaN/

Autonomous Orientation and Geolocation via Celestial Objects

Based on a hemispherical sensor geometry, a novel celestial navigation system is developed to use celestial objects to determine the absolute location and orientation information without the aid of satellites via two different approaches. The first approach employs a hemispherical arrangement of light intensity sensors to determine the vector to the dominant light source. We present the sensing system to measure the sun vector via least squares method and achieve the application of a low-cost, small-sized solar compass. The system is shown to work well under ideal conditions but is susceptible to noise and uncertainties in some situations. The second approach uses camera instead of light sensor, enabling the detection of celestial objects in a much more accurate and flexible fashion. An elaborate camera calibration was conducted to mitigate lens distortion and explore the transformation from image pixel coordinates to stationary world coordinates. With suitable image processing strategies, the system is able to use images of the sun and moon for the purpose of obtaining azimuth and zenith angles in spite of various disturbances. Given the results measured with our sensing systems, a generalized geolocation method is presented to estimate the absolute location on the earth. The approach, inspired by the traditional manual intercept method, automates all of its steps in an iterative fashion. It derives both the geolocation estimates and the error intervals based on measurement noise levels. This method is superior to most traditional approaches in that it derives the estimates even with lower quality sensors

Investigation of Context Determination for Advanced Navigation using Smartphone Sensors

Navigation and positioning is inherently dependent on the context, which comprises both the operating environment and the behaviour of the host vehicle or user. The environment determines the type and quality of radio signals available for positioning, while the behaviour can contribute additional information to the navigation solution. Although many navigation and positioning techniques have been developed, no single one is capable of providing reliable and accurate positioning in all contexts. Therefore, it is necessary for a navigation system to be able to operate across different types of contexts. Context adaptive navigation offers a solution to this problem by detecting the operating contexts and adopting different positioning techniques accordingly. This study focuses on context determination with the available sensors on smartphone, through framework design, behavioural and environmental context detection, context association, comprehensive experimental tests, and system demonstration, building the foundation for a context-adaptive navigation system. In this thesis, the overall framework of context determination is first designed. Following the framework, the behavioural contexts, covering different human activities and vehicle motions, are recognised by different machine learning classifiers in hierarchy. Their classification results are further enhanced by feature selection and a connectivity dependent filter. Environmental contexts are detected from GNSS measurements. Indoor and outdoor environments are first distinguished based on the availability and strength of GNSS signals using a hidden Markov model based method. Within the model, the different levels of connections between environments are exploited as well. Then a fuzzy inference system is designed to enable the further classification of outdoor environments into urban and open-sky. As behaviours and environments are not completely independent, this study also considers context association, investigating how behaviours can be associated within environment detection. Tests in a series of multi-context scenarios have shown that the association mechanism can further improve the reliability of context detection. Finally, the proposed context determination system has been demonstrated in daily scenarios