GNSS Precise Point Positioning Using Low-Cost GNSS Receivers

There are positioning techniques available such as Real-Time Kinematic (RTK) which allow user to obtain few cm-level positioning, but require infrastructure cost, i.e., setting up local or regional networks of base stations to provide corrections. Precise Point Positioning (PPP) using dual-frequency receivers is a popular standalone technique to process GNSS data by applying precise satellite orbit and clock correction along with other corrections to produce cm to dm-level positioning. At the time of writing, almost all low-cost and ultra-low-cost (few $10s) GNSS units are single-frequency chips. Single-frequency PPP poses challenges in terms of effectively mitigating ionospheric delay and the multipath, as there is no second frequency to remove the ionospheric delay. The quality of measurements also deteriorates drastically from geodetic-grade to ultra-low-cost hardware. Given these challenges, this study attempts to improve the performance of single-frequency PPP using geodetic-grade hardware, and to capture the potential positioning performance of this new generation of low-cost and ultra-low-cost GNSS chips. Raw measurement analysis and post-fit residuals show that measurements from cellphones are more prone to multipath compared to signals from geodetic-grade and low-cost receivers. Horizontal accuracy of a few-centimetres is demonstrated with geodetic-grade hardware. Whereas accuracy of few-decimetres is observed from low-cost and ultra-low-cost GNSS hardware. With multi-constellation processing, improvements in accuracy and reductions in convergence time over initial 60 minutes period, are also demonstrated with three different set of GNSS hardware. Horizontal and vertical rms of 37 cm and 51 cm, respectively, is achieved using a cellphone

Integer Ambiguity Resolution for Multi-GNSS and Multi-Signal Raw Phase Observations

The continuous modernisation of existing Global Navigation Satellite Systems (GNSS) and the development of new systems with a multitude of different carrier frequencies and a variety of signal modulations creates a true multi-GNSS and multi-signal environment available today. Still most precise GNSS processing strategies rely on dual-frequency measurements only by applying the Ionosphere-Free (IF) Linear Combination (LC) of GNSS observables and therefore do not benefit from the available multi-signal environment. While in this processing approach the first order effect of the ionospheric delay can be eliminated almost completely, the formation of linear combinations of GNSS observables leads to a noise increase for the resulting observations and a loss of some of the physical characteristics of the original signals, like the integer nature of the carrier phase ambiguity. In order to benefit from the multi-GNSS and multi-signal environment available today, the scientific analyses and precise applications presented in this work are based on the raw observation processing approach, which makes use of the original (raw) observations without forming any linear combinations or differences of GNSS observables. This processing strategy provides the flexibility to make use of all or a selection of available multi-GNSS and multi-signal raw observations, which are jointly processed in a single adjustment as there is no inherent limitation on the number of usable signals. The renunciation of linear combinations and observation differences preserves the physical characteristics of individual signals and implies that multi-signal biases and ionospheric delays need to be properly determined or corrected in the parameter estimation process. The raw observation processing approach is used in this work to jointly process measurements from up to three different GNSS, including eleven signals tracked on up to eight different carrier frequencies in one single adjustment. The bias handling for multi-GNSS and multi-signal applications is analysed with a focus on physically meaningful parameter estimates to demonstrate the benefits of handling clock offset parameters, multi-signal code biases and ionospheric delay estimates in a physically meaningful and consistent way. In this context, receiver-specific multi-GNSS and multisignal biases are analysed and calibrated by the use of a GNSS signal simulator. The disadvantages of eliminating physical characteristics due to the formation of linear combinations of observations or commonly used parameter estimation strategies are demonstrated and discussed. The carrier phase Integer Ambiguity Resolution (IAR) approach developed and implemented in the course of this work is based on the joint processing of multi-GNSS and multi-signal raw observations without forming any linear combinations or observation differences. Details of the implemented IAR approach are described and the performance is analysed for available carrier signal frequencies of different GNSS. Achieved results are compared to the conventional IAR approach based on IF linear combinations and the so called Widelane (WL) and Narrowlane (NL) ambiguities. In addition, the resolution of inter-system integer ambiguities is analysed for common GNSS signal frequencies. The performance of the implemented IAR approach is demonstrated and analysed by the joint Precise Orbit Determination (POD) of multi-GNSS satellites based on fixed multi-frequency carrier phase ambiguities. The improvement of the satellite orbit and clock quality by fixing raw observation ambiguities confirms the successful implementation of the IAR approach based on raw observation processing. Multi-GNSS satellite orbits and clock offsets determined with this approach are compared to results generated with the conventional IF linear combination processing approach and independent external products. This comparison demonstrates an at least equivalent performance of the implemented IAR approach based on raw observation processing. In addition, the fixed raw observation ambiguities are used to investigate and discuss characteristics of multi-GNSS and multi-frequency phase biases

Desarrollo de algoritmos para el tratamiento de datos GNSS : su aplicación a los escenarios GPS modernizado y Galileo

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Matemáticas, Sección Departamental de Física de la Tierra, Astronomía y Astrofísica I (Geofísica y Meteorología) (Astronomía y Geodesia), leída el 24-07-2012Nowadays, the major GNSS systems are the american GPS and the russian GLONASS, however, in a near future the european project Galileo and the chinesse system COMPASS will become part of the current GNSS scenario. These systems will transmit for the first time three different frequencies, giving place to a multi-system and multi-frequency scenario which will dramatically push the boundaries of the positioning techniques. Currently, one of the most studied positioning techniques is known as Precise Point Positioning (PPP), which is aimed at estimating precise receiver position from undifferenced GNSS code and carrier phase observations and precise satellite products. In this thesis, some new and original algorithms for static PPP have been developed, which are able to deal with the future multi-system and multifrequency GNSS observations. The new algorithms have been named MAP3. In the new approach, the least squares theory is applied twice to estimate the ionospheric delay, initial ambiguities and smoothed pseudodistances from undifferenced observations, which in turn are used to recover the receiver position and its clock offset. MAP3 provides position estimations with an accuracy of 2.5 cm after 2 hours observation and 7 mm in 1 day, being at the same level as other PPP programs and even better results are obtained with MAP3 in short observation periods. Moreover, MAP3 have provided some of the first results in positioning from GIOVE observations and GPC products. In addition, these algorithms have been applied in the analysis of the influence of ionospheric disturbances on the point positioning, concluding that the presence of a high ROT (Rate of TEC), observed at equatorial latitudes, reflects a significant degradation of the point positioning from dual-frequency observations.Actualmente, los únicos sistemas globales de navegación por satélites operativos son GPS y GLONASS, sin embargo, en un futuro cercano el proyecto europeo Galileo y el sistema chino COMPASS entrarán a formar parte del actual escenario GNSS. Estos sistemas emplearán por primera vez, tres frecuencias distintas, dando lugar a un escenario multi-frecuencia que revolucionará las técnicas de posicionamiento. Entre las técnicas actuales de posicionamiento con GNSS destaca el Posicionamiento Preciso Puntual (PPP), que consiste en determinar la posición de un receptor a partir de observaciones de código y fase no differenciadas y productos precisos. En este trabajo de tesis se han desarrollado unos nuevos y originales algoritmos para PPP estático, llamados MAP3, capaces de procesar observaciones GNSS multifrecuencia y multi-sistema del futuro escenario GNSS y determinar la posición de un receptor de forma precisa y exacta. Los algoritmos MAP3 se dividen en dos partes en las cuales se ha aplicado la teoría mínimos cuadrados y se han obtenido expresiones explícitas para estimar el retraso ionosférico, ambigüedades de fase inicial y pseudodistancias suavizadas, que se emplean para determinar la posición del receptor y el offset de su reloj. MAP3 proporciona una estimación de la posición con una exactitud de 2.5 cm tras 2 horas de observación y de 7 mm tras 24 h, resultados que mejoran los obtenidos hasta el momento con otros programas para PPP en periodos cortos de tiempo. Además, MAP3 han proporcionado los primeros resultados en el posicionamiento con observaciones GIOVE y productos del GPC. Por otro lado, estos algoritmos se han aplicado al análisis de los efectos de ciertas perturbaciones ionosféricas en el posicionamiento concluyendo que la presencia de un ROT (Rate of TEC) elevado, observado en latitudes ecuatoriales, refleja una degradación significativa del posicionamiento puntual con observaciones doble frecuencia.Unidad Deptal. de Astronomía y GeodesiaFac. de Ciencias MatemáticasTRUEunpu

Precise Orbit Determination of CubeSats

CubeSats are faced with some limitations, mainly due to the limited onboard power and the quality of the onboard sensors. These limitations significantly reduce CubeSats' applicability in space missions requiring high orbital accuracy. This thesis first investigates the limitations in the precise orbit determination of CubeSats and next develops algorithms and remedies to reach high orbital and clock accuracies. The outputs would help in increasing CubeSats' applicability in future space missions

The use of unmanned aerial vehicles (UAVs) for engineering geology applications

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Ionospheric Regional modeling Algorithm based on GNSS Precise Point Positioning

Precise point positioning (PPP) is an absolute spatial positioning technology different from carrier phase relative positioning. With the continuous development of Global navigation satellite system (GNSS), multi-constellation GNSS further provides PPP with more abundant observation information and useful spatial geometric observations, which improves positioning performance and robustness. In recent years, the un-difference and un-combined precise point positioning (UPPP) has been continuously developing. Firstly, we introduce the basic theory of GNSS positioning and compare the position performance between UPPP and ionospheric-free PPP (IF PPP). The positioning performance of the four mainstream GNSS systems, GPS, GLONASS, Galileo, and Beidou, the PPP floating-point solutions of the four satellite systems all converge within 60 minutes and their error are less than 10cm. Secondly, a two-dimensional (2-d) model is proposed to fit the vertical total electronic content (VTEC) in the ionosphere with the ionospheric delays extracted by UPPP. With the model constraining the ionospheric delay in UPPP, the convergence is 2 minutes shorter than using the global ionospheric map (GIM) from IGS. Thirdly, to solve the limitation of the traditional methods in 2d representation, a method is proposed represent the ionosphere in 3D, called Compressed Sensing Tomography (CST). Comparing the simulated single-difference slant total electron content (STEC) and the input single- difference STEC between satellites, the root mean square (RMS) of the reference station’s error is less than 1 TEC uni

Evaluating indoor positioning systems in a shopping mall : the lessons learned from the IPIN 2018 competition

The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future

Multi-environment Georeferencing of RGB-D Panoramic Images from Portable Mobile Mapping – a Perspective for Infrastructure Management

Hochaufgelöste, genau georeferenzierte RGB-D-Bilder sind die Grundlage für 3D-Bildräume bzw. 3D Street-View-Webdienste, welche bereits kommerziell für das Infrastrukturmanagement eingesetzt werden. MMS ermöglichen eine schnelle und effiziente Datenerfassung von Infrastrukturen. Die meisten im Aussenraum eingesetzten MMS beruhen auf direkter Georeferenzierung. Diese ermöglicht in offenen Bereichen absolute Genauigkeiten im Zentimeterbereich. Bei GNSS-Abschattung fällt die Genauigkeit der direkten Georeferenzierung jedoch schnell in den Dezimeter- oder sogar in den Meterbereich. In Innenräumen eingesetzte MMS basieren hingegen meist auf SLAM. Die meisten SLAM-Algorithmen wurden jedoch für niedrige Latenzzeiten und für Echtzeitleistung optimiert und nehmen daher Abstriche bei der Genauigkeit, der Kartenqualität und der maximalen Ausdehnung in Kauf. Das Ziel dieser Arbeit ist, hochaufgelöste RGB-D-Bilder in verschiedenen Umgebungen zu erfassen und diese genau und zuverlässig zu georeferenzieren. Für die Datenerfassung wurde ein leistungsstarkes, bildfokussiertes und rucksackgetragenes MMS entwickelt. Dieses besteht aus einer Mehrkopf-Panoramakamera, zwei Multi-Beam LiDAR-Scannern und einer GNSS- und IMU-kombinierten Navigationseinheit der taktischen Leistungsklasse. Alle Sensoren sind präzise synchronisiert und ermöglichen Zugriff auf die Rohdaten. Das Gesamtsystem wurde in Testfeldern mit bündelblockbasierten sowie merkmalsbasierten Methoden kalibriert, was eine Voraussetzung für die Integration kinematischer Sensordaten darstellt. Für eine genaue und zuverlässige Georeferenzierung in verschiedenen Umgebungen wurde ein mehrstufiger Georeferenzierungsansatz entwickelt, welcher verschiedene Sensordaten und Georeferenzierungsmethoden vereint. Direkte und LiDAR SLAM-basierte Georeferenzierung liefern Initialposen für die nachträgliche bildbasierte Georeferenzierung mittels erweiterter SfM-Pipeline. Die bildbasierte Georeferenzierung führt zu einer präzisen aber spärlichen Trajektorie, welche sich für die Georeferenzierung von Bildern eignet. Um eine dichte Trajektorie zu erhalten, die sich auch für die Georeferenzierung von LiDAR-Daten eignet, wurde die direkte Georeferenzierung mit Posen der bildbasierten Georeferenzierung gestützt. Umfassende Leistungsuntersuchungen in drei weiträumigen anspruchsvollen Testgebieten zeigen die Möglichkeiten und Grenzen unseres Georeferenzierungsansatzes. Die drei Testgebiete im Stadtzentrum, im Wald und im Gebäude repräsentieren reale Bedingungen mit eingeschränktem GNSS-Empfang, schlechter Beleuchtung, sich bewegenden Objekten und sich wiederholenden geometrischen Mustern. Die bildbasierte Georeferenzierung erzielte die besten Genauigkeiten, wobei die mittlere Präzision im Bereich von 5 mm bis 7 mm lag. Die absolute Genauigkeit betrug 85 mm bis 131 mm, was einer Verbesserung um Faktor 2 bis 7 gegenüber der direkten und LiDAR SLAM-basierten Georeferenzierung entspricht. Die direkte Georeferenzierung mit CUPT-Stützung von Bildposen der bildbasierten Georeferenzierung, führte zu einer leicht verschlechterten mittleren Präzision im Bereich von 13 mm bis 16 mm, wobei sich die mittlere absolute Genauigkeit nicht signifikant von der bildbasierten Georeferenzierung unterschied. Die in herausfordernden Umgebungen erzielten Genauigkeiten bestätigen frühere Untersuchungen unter optimalen Bedingungen und liegen in derselben Grössenordnung wie die Resultate anderer Forschungsgruppen. Sie können für die Erstellung von Street-View-Services in herausfordernden Umgebungen für das Infrastrukturmanagement verwendet werden. Genau und zuverlässig georeferenzierte RGB-D-Bilder haben ein grosses Potenzial für zukünftige visuelle Lokalisierungs- und AR-Anwendungen

Multi-frequency and multi-GNSS PPP phase bias estimation and ambiguity resolution

Multi-frequency and multi-GNSS measurements from modernized satellites are properly integrated for PPP with ambiguity resolution to achieve the state-of-the-art fast and accurate positioning, which provides an important contribution to GNSS precise positioning and applications. The multi-frequency and multi-GNSS PPP phase bias estimation and ambiguity resolution, which is accomplished by a unified model based on the uncombined PPP, are thoroughly evaluated with special focus on Galileo and BDS