The Importance of Human Motion for Simulation Testing of GNSS

Human motion is generally considered benign to the performance of global navigation satellite system (GNSS) and other positioning sensors. This study proves that this is not the case, even for typical human behaviour involving GNSS user equipment, e.g. in smartphones. Using recorded human motion, it is shown that phase-lock loops (PLLs) in GNSS receivers are sensitive to jerk dynamics induced by user motion, resulting in carrier cycle slips. To test the effects of human dynamics on GNSS carrier tracking, real human motion profiles were captured. These profiles comprised typical types of movements using a mobile phone, e.g. holding, answering and texting, different types of activities, e.g. walking or jogging, as well as different phone locations on the human body, e.g. in a hand, pocket, backpack and on an arm band. The data were captured outdoors using an Xsens MTi-G MEMS (Micro-Electronic Mechanical Systems) Inertial Measurement Unit (IMU) aided by a Global Positioning System (GPS) receiver with a 100Hz output rate. Then the captured motion (MoCap) was processed and input into a simulated PLL in Matlab with different tracking loop bandwidths (BL_CA) and carrier power-to-noise density ratios (C/N0). The results show that pedestrian gestures and type of activity, e.g. walking or jogging, affect the performance of the simulated PLL more adversely than the location of the phone on the human body. Also, to track pedestrian motion encompassing these gestures, activities and receiver locations, a minimum of 15Hz tracking bandwidth is required. Consequently, receiver manufacturers should exercise caution before reducing tracking bandwidths to compensate for the reduction in C/N0 resulting from GNSS antenna design, human body masking and the effects of buildings, trees and other environmental features. This paper also proposes and describes a pedestrian motion model (PMM) that simulates the GNSS antenna trajectory in 3D, when it is held by or attached to a pedestrian. The PMM will be validated using real MoCap scenarios and will enable Spirent to increase their product offering in the area of simulation-based testing of positioning sensors for pedestrian applications by generating human motion profiles which affect realistically the performance of GNSS user equipment

Time and Frequency Transfer in a Coherent Multistatic Radar using a White Rabbit Network

Networks of coherent multistatic radars require accurate and stable time and frequency transfer (TFT) for range and Doppler estimation. TFT techniques based on global navigation satellite systems (GNSS), have been favoured for several reasons, such as enabling node mobility through wireless operation, geospatial referencing, and atomic clock level time and frequency stability. However, such systems are liable to GNSS-denial, where the GNSS carrier is temporarily or permanently removed. A denial-resilient system should consider alternative TFT techniques, such as the White Rabbit (WR) project. WR is an Ethernet based protocol, that is able to synchronise thousands of nodes on a fibre-optic based network with sub-nanosecond accuracy and picoseconds of jitter. This thesis evaluates WR as the TFT network for a coherent multistatic pulse-Doppler radar – NeXtRAD. To test the hypothesis that WR is suitable for TFT in a coherent multistatic radar, the time and frequency performance of a WR network was evaluated under laboratory conditions, comparing the results against a network of multi-channel GPS-disciplined oscillators (GPSDO). A WR-disciplined oscillator (WRDO) is introduced, which has the short-term stability of an ovenised crystal (OCXO), and long-term stability of the WR network. The radar references were measured using a dual mixer time difference technique (DMTD), which allows the phase to be measured with femtosecond level resolution. All references achieved the stringent time and frequency requirements for short-term coherent bistatic operation, however the GPSDOs and WRDOs had the best short-term frequency stability. The GPSDOs had the highest amount of long-term phase drift, with a peak-peak time error of 9.6 ns, whilst the WRDOs were typically stable to within 0.4 ns, but encountered transient phase excursions to 1.5 ns. The TFT networks were then used on the NeXtRAD radar, where a lighthouse, Roman Rock, was used as a static target to evaluate the time and frequency performance of the references on a real system. The results conform well to the laboratory measurements, and therefore, WR can be used for TFT in coherent radar

Estimation Techniques and Mitigation Tools for Ionospheric effects on GNSS Receivers

Navigation is defined as the science of getting a craft or person from one place to another. The development of radio in the past century brought fort new navigation aids that enabled users, or rather their receivers, to compute their position with the help of signals from one or more radio-navigation system . The U.S. Global Positioning System (GPS) was envisioned as a satellite system for three-dimensional position and velocity determination fulfilling the following key attributes: global coverage, continuous/all weather operation, ability to serve high-dynamic platforms, and high accuracy. It represents the fruition of several technologies, which matured and came together in the second half of the 20th century. In particular, stable space-born platforms, ultra-stable atomic frequency standards, spread spectrum signaling, and microelectronics are the key developments in the realization and success of GPS. While GPS was under development, the Soviet Union undertook to develop a similar system called GLObalnaya NAvigatsionnaya Sputnikovaya Sistema (GLONASS). Both GLONASS and GPS were designed primarily for the military, but have transitioned in the past decades towards providing civilian and Safety-of-Life services as well. Other Global Navigation Satellite Systems (GNSS) are now being developed and deployed by governments, international consortia, and commercial interests. Among these are the European system Galileo and the Chinese system Beidou. Other regional systems are the Japanese Quasi-Zenith Satellite System and the Indian Gagan. GNSS have become a crucial component in countless modern systems, e.g. in telecommunication, navigation, remote sensing, precise agriculture, aviation and timing. One of the main threats to the reliable and safe operation of GNSS are the variable propagation conditions encountered by GNSS signals as they pass through the upper atmosphere of the Earth. In particular, irregular concentration of electrons in the ionosphere induce fast fluctuations in the amplitude and phase of GNSS signals called scintillations. The latter can greatly degrade the performance of GNSS receivers, with consequent economical impacts on service providers and users of high performance applications. New GNSS navigation signals and codes are expected to help mitigate such effects, although to what degree is still unknown. Furthermore, these new technologies will only come on line incrementally over the next decade as new GNSS satellites become operational. In the meantime, GPS users who need high performance navigation solution, e.g., offshore drilling companies, might be forced to postpone operations for which precision position knowledge is required until the ionospheric disturbances are over. For this reason continuous monitoring of scintillations has become a priority in order to try to predict its occurrence. Indeed, it is a growing scientific and industrial activity. However, Radio Frequency (RF) Interference from other telecommunication systems might threaten the monitoring of scintillation activity. Currently, the majority of the GNSS based application are highly exposed to unintentional or intentional interference issues. The extremely weak power of the GNSS signals, which is actually completely buried in the noise floor at the user receiver antenna level, puts interference among the external error contributions that most degrade GNSS performance. It is then of interest to study the effects these external systems may have on the estimation of ionosphere activity with GNSS. In this dissertation, we investigate the effect of propagation issues in GNSS, focusing on scintillations, interference and the joint effect of the two phenomena

Test bench solutions for advanced GNSS receivers : implementation, automation, and application

Considerable study has been devoted to the implementation of GNSS receivers for diverse applications, and to finding solutions to some of the non-idealities associated with such receivers. However, not much research is devoted to innovations in their performance evaluation, even though this is an integral step in the overall implementation process. This research work attempts to address this issue through three different perspectives: by focusing on innovation in the testing procedures and test-bench implementation, its automation and its application to advanced multi-frequency, multi-constellation GPS and Galileo receivers. Majority of this research was conducted within the GREAT, GRAMMAR, and FUGAT projects funded by EU FP6/FP7 and TEKES respectively, during which the author was responsible for designing test-scenarios and performing validations of the implemented receiver solution. The first part of the research is devoted to the study and design of sources of test signals for an advanced GNSS receiver test-bench. An in-depth background literature study was conducted on software-based GNSS signal simulators to trace their evolution over the past two decades. Keeping their special features and limitations in view, recommendations have been made on the optimum architecture and essential features within such simulators for testing of advanced receivers. This resulted in the implementation of an experimental software-based simulator capable of producing GPS L1 and Galileo E1 signals at intermediate frequency. Another solution investigated was a GNSS Sampled Data Generator (SDG) based on wideband sampling. This included designing the entire radio front-end operating on the bandpass-sampling principle. The low noise amplifier designed as part of this SDG has been implemented on a printed circuit board. Phase noise (PN) from the radio front-end’s local frequency generator (LFG) is a source of error that has hitherto not been included in any GNSS signal simulator. Furthermore, the characterization of the baseband tracking loops in presence of this phase noise has not yet been included in the typical receiver test scenarios. The second part of this research attempts to create mathematical models representing the LFG’s phase noise contribution, first for a free running oscillator and later for a complete phase-locked loop (PLL). The effect of such phase noise was studied on the baseband correlation performance of GPS and Galileo receivers. The results helped to demonstrate a direct relation between the PN and the baseband tracking performance, thus helping to define guidelines for radio front-end PLL circuit design in order to maintain a minimum baseband tracking performance within the GNSS receiver. The final part of this research work focusses on describing the automated test-bench developed at Tampere University of Technology (TUT) for analyzing the overall performance of multi-frequency multi-constellation GNSS receivers. The proposed testbench includes a data capture tool to extract internal process information, and the overall controlling software, called automated performance evaluation tool, that is able to communicate between all modules for hands-free, one-button-click testing of GNSS receivers. Furthermore, these tools have been applied for the single frequency GPS L1 performance testing of the TUTGNSS receiver, with recommendations on how they can be adapted to testing of advanced multi-frequency, multi-constellation receivers

Advanced Tracking Loop Architectures for Multi-frequency GNSS Receiver

The multi-frequency Global Navigation Satellite System (GNSS) signals are designed to overcome the inherent performance limitations of single-frequency receivers. However, the processing of multiple frequency signals in a time-varying GNSS signal environment which are potentially affected by multipath, ionosphere scintillation, blockage, and interference is quite challenging, as each signal is influenced differently by channel effects according to its Radio Frequency (RF). In order to get benefit of synchronously/coherently generated multiple frequency signals, advanced receiver signal processing techniques need to be developed.The aim of this research thesis is to extract the best performance benefits out of multifrequency GNSS signals in a time-varying GNSS signal environment. To accomplish this objective, it is necessary to analyze the multi-frequency signal characteristics and to investigate suitable signal processing algorithms in order to enable the best performance of each signal. The GNSS receiver position accuracy and reliability are majorly determined by the signal tracking-loop performance, hence, the primary focus of this thesis is on improving the tracking-loop performance of coherently generated multi-frequency signals.In the first phase of this research, the performance of multi-frequency GNSS signals is analyzed using conventional signal processing algorithms. Furthermore, the performance of a combination of multi-frequency signals is evaluated in order to find the optimum two-frequency signal combination for standalone and differential positioning applications. The limitations of the conventional multi-frequency signal processing algorithms are identified and an optimum dual-frequency signal processing architecture is proposed for robust and precise positioning applications.By making use of the inherent linear relation between the Line-of-Sight (LOS) Doppler shifts of multi-frequency GNSS signals, a computationally efficient Centralized Dynamics Tracking Loop (CTL) architecture is also proposed. In the CTL architecture, the common geometric Doppler shift in the received multi-frequency signals is estimated using a higher-order wide-band filter by making use of multiple frequency channel measurements in a coordinated manner. Additionally, the residual-phase variations specific to each frequency channel are tracked using Phase Lock Loop (PLL) with a narrow bandwidth filter. The CTL filter provides the geometric Doppler shift aid to individual frequency channels. The common Doppler-aided narrow-band signal tracking enhances the signal tracking sensitivity and robustness to the in-band interference in each frequency channel. This further reduces the noise in the linear combination of pseudorange observations.In real GNSS signal environment, multiple frequency signals are often subjected to intentional or unintentional RF interference either at the same time or at different time instants. Moreover, each of these signals is influenced differently by RF interference. To track signals in such time-varying signal conditions, the CTL using an Adaptive Kalman Filter (AKF) is proposed to enable an adaptive tracking loop bandwidth in response to received signal power level and signal dynamics. The central task of the AKF is to effectively blend multiple frequency carrier-phase observations to estimate the common geometric Doppler frequency of received multiple frequency signals. A suitable collaboration in multi-frequency channel tracking using centralized dynamics tracking loop enables a robust carrier tracking even if some of the frequency channels are affected by ionospheric scintillation, multipath, or interference.The performance of the proposed multi-frequency GNSS signal processing algorithms is demonstrated using analytical methods and experimental results based on live satellite data collected over GPS L1, L2C, and L5 signal frequencies. The dual-frequency signal processing architecture proposed in this research thesis has reduced the position error by 50%. The centralized dynamics multi-frequency carrier tracking loop has enhanced the individual channel tracking loop threshold by 7 dB in challenging signal conditions

Centralized dynamics multi‐frequency GNSS carrier synchronization

In this article, we propose a new centralized multi‐frequency carrier tracking architecture using an adaptive Kalman filter to enhance the loop sensitivity and reliability of individual signal tracking in challenging signal environments. The main task of the centralized dynamics‐tracking filter is to effectively blend multiple frequency carrier phase observations in order to estimate the common geometric Doppler frequency of multiple‐frequency received signals. Conventionally, multi‐frequency signals are tracked independently with a fixed‐loop noise bandwidth tracking approach, which is suboptimal in time‐varying signal environments. A suitable collaboration in multiple‐frequency signal tracking using a centralized dynamics‐tracking loop enables robust carrier tracking even if some of the frequency channels are affected by ionospheric scintillation, carrier‐phase multipath, or interference. Additionally, computational efficiency of the multiple‐frequency tracking improves by using the proposed tracking loop architecture. Performance of the proposed multi‐frequency tracking‐loop architecture is verified with experiments using live multi‐frequency satellite signals collected from GPS Block‐IIF satellites under the influence of frequency‐selective interference signals

A GNSS Signal Simulator and Processor for Evaluating Acquisition and Tracking of GPS-like Signals From Satellites in LEO

Global navigation satellite systems (GNSS) have enabled accurate position, navigation, and timing (PNT) to both civilian and military users for a variety of applications. Since it has become a critical part of today's infrastructure, it is important to investigate ways to enhance or replace this service in challenging environments. These include urban canyons and indoor environments, as well as nefarious attacks, such as jamming and spoofing. Emerging low Earth orbiting (LEO) mega-constellations can be used to augment GNSS. These constellations contain a large number of satellites in order to provide global internet coverage. Although they are not optimized for PNT and use unknown signal structures, several research groups have already demonstrated the ability to track these signals and obtain position and time estimates. This thesis presents LEO signal simulation, acquisition and tracking using an in-house, Julia-language-based package, called GNSSTools. Topics included are an overview of GNSS, signal simulation and processing methods, and evaluation. Evaluations demonstrate the self-consistency of GNSSTools, and show its ability to process GPS L1 C/A and L5 simulated signals and data samples. Additionally, GPS signals are simulated with Doppler effects similar to signals observed from satellites in LEO to determine their effect on standard acquisition and tracking methods.</p

Optimization of demodulation performance of the GPS and GALILEO navigation messages

La performance de démodulation des signaux GNSS existants, GPS L1 C/A, L2C ou L5, est satisfaisante en environnements ouverts où le C/N0 disponible est assez élevé. Cependant, en milieu urbain, le niveau de C/N0 du signal reçu est souvent très bas et est affecté de variations rapides qui peuvent nuire la démodulation des messages GNSS. Donc, car les applications du marché de masse sont appelées à être déployées dans ces environnements, il est nécessaire d'étudier et de chercher des méthodes de démodulation/décodage qui améliorent la performance de démodulation des messages GNSS dans ces environnements. Il est aussi nécessaire de considérer les nouveaux signaux GPS L1C et GALILEO E1. Ces signaux doivent fournir un service de positionnement par satellite dans tout type d'environnement, et spécifiquement en milieu urbain. Ainsi, cette thèse analyse aussi les performances de démodulation des nouveaux signaux GNSS tels que définis dans les documents publics actuels. De plus, de nouvelles structures de message GALILEO E1 sont proposées et analysées afin d'optimiser la performance de démodulation ainsi que la quantité d'information diffusée. En conséquence, le but principal de cette thèse est d'analyser et améliorer la performance de démodulation des signaux GNSS ouverts au public, spécifiquement en milieu urbain, et de proposer de nouvelles structures de messages de navigation pour GALILEO E1. La structure détaillée des chapitres de cette thèse est donnée ci-après. En premier lieu, le sujet de cette thèse est introduit, ses contributions originales sont mises en avant, et le plan du rapport est présenté. Dans le 2ième chapitre, la thèse décrit la structure actuelle des signaux GNSS analysés, en se concentrant sur la structure du message de navigation, les codages canal implantés et leurs techniques de décodage. Dans le 3ième chapitre, deux types de modèles de canal de propagation sont présentés pour deux différents types de scénarios. D'un côté, un canal AWGN est choisi pour modéliser les environnements ouverts. De l'autre côté, le modèle mathématique de Perez-Fontan d'un canal mobile est choisi pour représenter les environnements urbains et indoor. Dans le 4ième chapitre, une tentative pour effectuer une prédiction binaire d'une partie du message de navigation GPS L1 C/A est présentée. La prédiction est essayée en utilisant les almanachs GPS L1 C/A, grâce à un programme de prédiction à long terme fourni par TAS-F, et des méthodes de traitement du signal: estimation spectrale, méthode de PRONY et réseau de neurones. Dans le 5ème chapitre, des améliorations à la performance de démodulation du message de GPS L2C et L5 sont apportées en utilisant leur codage canal de manière non traditionnelle. Deux méthodes sont analysées. La première méthode consiste à combiner les codages canal internes et externes du message afin de corriger davantage de mots reçus. La deuxième méthode consiste à utiliser les probabilités des données d'éphémérides afin d'améliorer le décodage traditionnel de Viterbi. Dans le 6ième chapitre, la performance de démodulation des messages de GPS L1C et du Open Service GALILEO E1 est analysée dans différents environnements. D'abord, une étude de la structure de ces deux signaux est présentée pour déterminer le C/N0 du signal utile reçu dans un canal AWGN. Puis, la performance de démodulation de ces signaux est analysée grâce à des simulations dans différents environnements, avec un récepteur se déplaçant à différentes vitesses et avec différentes techniques d'estimation de la phase porteuse du signal. ABSTRACT : The demodulation performance achieved by any of the existing GPS signals, L1 C/A, L2C or L5, is satisfactory in open environments where the available C/N0 is quite high. However, in indoor/urban environments, the C/N0 level of the received signal is often very low and suffers fast variations which can further affect the GNSS messages demodulation. Therefore, since the mass-market applications being designed nowadays are aimed at these environments, it is necessary to study and to search alternative demodulation/decoding methods which improve the GNSS messages demodulation performance in these environments. Moreover, new GNSS signals recently developed, such as GPS L1C and GALILEO E1, must also be considered. These signals aim at providing satellite navigation positioning service in any kind of environment, giving special attention to indoor and urban environments. Therefore, the demodulation performances of the new GNSS signals as they are defined in the current public documents is also analysed. Moreover, new GALILEO E1 message structures are proposed and analysed in order to optimize the demodulation performance as well as the quantity of broadcasted information. Therefore, the main goal of this dissertation is to analyse and to improve the demodulation performance of the current open GNSS signals, specifically in indoor and urban environments, and to propose new navigation message structures for GALILEO E1. A detailed structure of this dissertation sections is given next. First, the subject of this thesis is introduced, original contributions are highlighted, and the outline of the report is presented. Second, this dissertation begins by a description of the current structure of the different analysed GNSS signals, paying special attention to the navigation message structure, implemented channel code and their decoding techniques. In the third section, two types of transmission channel models are presented for two different types of environments. On one hand, an AWGN channel is used to model the signal transmission in an open environments. On the other hand, the choice of a specific mobile channel, the Perez-Fontan channel model, is chosen to model the signal transmission in an urban environment. In the fourth section, a tentative to make a binary prediction of the broadcasted satellite ephemeris of the GPS L1 C/A navigation message is presented. The prediction is attempted using the GPS L1 C/A almanacs data, a long term orbital prediction program provided by TAS-F, and some signal processing methods: spectral estimation, the PRONY method, and a neural network. In the fifth section, improvements to the GPS L2C and GPS L5 navigation message demodulation performance are brought by using their channel codes in a non-traditional way. Two methods are inspected. The first method consists in sharing information between the message inner and outer channel codes in order to correct more received words. The second method consists in using the ephemeris data probabilities in order to improve the traditional Viterbi decoding. In the sixth section, the GPS L1C and GALILEO E1 Open Service demodulation performance is analysed in different environments. First, a brief study of the structure of both signals to determine the received C/N0 in an AWGN channel is presented. Second, their demodulation performance is analysed through simulations in different environments, with different receiver speeds and signal carrier phase estimation techniques

Adaptive Estimation of Signals of Opportunity

To exploit unknown ambient radio frequency signals of opportunity (SOPs) for positioning and navigation, one must estimate their states along with a set of parameters that characterize the stability of their oscillators. SOPs can be modeled as stochastic dynamical systems driven by process noise. The statistics of such process noise is typically unknown to the receiver wanting to exploit the SOPs for positioning and navigation. Incorrect statistical models jeopardize the estimation optimality and may cause filter divergence. This necessitates the development of adaptive filters, which provide a significant improvementover fixed filters through the filter learning process. This paper develops two such adaptive filters: an innovationbased maximum likelihood filter and an interacting multiple model filter and compares their performance and complexity. Numerical and experimental results are presented demonstrating the superiority of these filters over fixed, mismatched filters.Aerospace Engineering and Engineering Mechanic