211 research outputs found

    Dataan perustuvat voimamallit GNSS satelliittien rataennustuksissa

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    In this study, we consider the problem of predicting the orbit of a GNSS satellite with a force model that can be adjusted based on data. In autonomous prediction, the goal is to use the positioning device in a completely or mostly autonomous mode. For this, the usable time of broadcast ephemeris need to be extended and to this end, predicting the orbit of a satellite is necessary. This is done by creating a force model for the satellite. In our previous research, the force model was based on four largest forces acting on a satellite: the gravitation of the Earth, the Sun and the Moon and solar radiation pressure. The position of the satellite in the future can then be computed by integrating the equation of motion with certain initial conditions. The goal of this study was to improve the existing model by adding forces that can be estimated on the positioning device based on received data. This is done with latent force models, where additional forces have some prior model and need to be more accurately estimated with machine learning techniques. We create a state- space model for the latent forces, which is combined with the state-space model of the analytical motion of the satellite. Received broadcast ephemerides can then be used to estimate these forces in addition to position and velocity of a satellite. This is done as statistical inference with filtering and smoothing methods. The main result of this study was that even a relatively simple model can improve prediction accuracy by a significant amount. After the largest forces have been taken into account, the largest improvement comes from a data-driven approach rather than adding more analytical terms to the force model. We created an adaptive algorithm, where data from a new broadcast can be used to update the estimates for the latent forces, which can then be used to predict the position of the satellite more accurately. Our model worked with all tested constellations: GPS, GLONASS and Beidou. The improvement was biggest with GPS and Beidou MEO satellites, while GLONASS satellites did not show as much improvement

    Adaptive filtering applications to satellite navigation

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    PhDDifferential Global Navigation Satellite Systems employ the extended Kalman filter to estimate the reference position error. High accuracy integrated navigation systems have the ability to mix traditional inertial sensor outputs with navigation satellite based position information and can be used to develop high accuracy landing systems for aircraft. This thesis considers a host of estimation problems associated with aircraft navigation systems that currently rely on the extended Kalman filter and proposes to use a nonlinear estimation algorithm, the unscented Kalman filter (UKF) that does not rely on Jacobian linearisation. The objective is to develop high accuracy positioning algorithms to facilitate the use of GNSS or DGNSS for aircraft landing. Firstly, the position error in a typical satellite navigation problem depends on the accuracy of the orbital ephemeris. The thesis presents results for the prediction of the orbital ephemeris from a customised navigation satellite receiver's data message. The SDP4/SDP8 algorithms and suitable noise models are used to establish the measured data. Secondly, the differential station common mode position error not including the contribution due to errors in the ephemeris is usually estimated by employing an EKF. The thesis then considers the application of the UKF to the mixing problem, so as to facilitate the mixing of measurements made by either a GNSS or a DGNSS and a variety of low cost or high-precision INS sensors. Precise, adaptive UKFs and a suitable nonlinear propagation method are used to estimate the orbit ephemeris and the differential position and the navigation filter mixing errors. The results indicate the method is particularly suitable for estimating the orbit ephemeris of navigation satellites and the differential position and navigation filter mixing errors, thus facilitating interoperable DGNSS operation for aircraft landing

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

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    Das Verfahren des GNSS Precise Point Positioning unter Anwendung des Ă„quivalenzprinzips

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    In the last decade Precise Point Positioning (PPP) has become a powerful and widely used technique for positioning by means of Global Navigation Satellite System (GNSS) in geodetic/scientific and civil/daily applications. Meanwhile, the equivalence principle of GNSS data processing has been developed and can now be easily explained and accepted since it was firstly algebraically pointed out in 2002. The objective of this thesis is to explore high-performance PPP algorithms and to develop GNSS algorithms with application of the equivalence principle. The core research and contributions of this thesis are summarized as follows. In this thesis it is the first time that the specific equivalence of un-differenced and time differencing PPP algorithms is proved theoretically on the basis of the equivalence principle and the equivalence property of un-differenced and differencing algorithms. Meanwhile, as a supplement to the equivalence property of the triple differences, an alternative method is proposed and derived to prove the equivalence between triple differences and zero-difference which up to now was missing. As a consequence of above conducted theoretical study, a time differencing PPP algorithm based on the equivalence principle is derived and can be used to obtain the coordinates difference and average velocity between two adjacent epochs. Such a time differencing PPP algorithm is able to provide both position and velocity results from the phase and code observations and is expected to be beneficial for applications, such as airborne gravimetry or earthquake monitoring, and could also be an efficient method to detect cycle slips in data processing. The influence of tropospheric delay on PPP, especially in the context of observations in the polar region or with low elevation cut-off angles, where the position results of the observations are more significantly affected by tropospheric delay, is analyzed and a methodology for minimizing its effect is proposed. Actual meteorological data are used and proved to be beneficial for improving PPP precision in the Antarctic region. The effect of tropospheric horizontal gradient correction on PPP is also analyzed and verified to remarkably improve PPP precision under lower elevation cut-off angles and higher humidity conditions. A priori constrained PPP algorithms are proposed and derived in this thesis to improve the efficiency and precision of PPP. The a priori information concerning the geometric and physical properties of observations, which is known with a certain a priori precision, is applied in the PPP algorithms. The contribution of different a priori information constraints on different parameters to PPP solution is analyzed and validated. The a priori constraints as employed in the PPP are specified according to coordinates-, receiver clock offset-, tropospheric delay- and ambiguities-constraints, respectively. The validation of the derived PPP algorithms shows a significant improvement concerning convergence time and positioning accuracy. Moreover, the applications of different constraints under specific conditions are discussed and validated. A multi-constellation combined PPP algorithm based on the equivalence principle is proposed and derived in this thesis. With such an algorithm, the exponentially increased computational load of the traditional multi-GNSS PPP algorithm can be reduced to the single linear increase when more GNSS satellites are available and used for combined computation. In case of GPS/BDS combination, a method which can speed up the determination of the ambiguities parameters of BDS through applying the contribution of GPS observations is proposed to significantly reduce the convergence time in BDS PPP. The GPS/BDS combined PPP algorithm with inter-system bias (ISB) parameter is also derived. Using the estimated ISB as a priori constraint in the GPS/BDS combined PPP is proposed. The result demonstrates that the a priori constraint of ISB shows superiority in the convergence time of PPP processing and can mainly improve the positioning accuracy in E component. In traditional combined PPP it is difficult to adaptively adjust the contribution of each single system to the combination through constructing total calculation, and it will lead to the deterioration in the combination accuracy. In this context, the adaptively combined PPP algorithms based on the equivalence principle are proposed and derived, which can easily achieve an adaptive adjustment of weight ratio of each system in the multi-GNSS combination. By using the posteriori covariance matrix of the shared parameters of each single system and the Helmert variance components to adaptively adjust the weight ratio of each system, the derived algorithms can improve the accuracy of combination significantly, compared to combined PPP with identical weight ratio. The developed algorithms are net applicable and can be used for cloud computation for internet GNSS service which is considered relevant for possible commercial applications.In den letzten zehn Jahren entwickelte sich das Verfahren des Precise Point Positioning (PPP) zu einer leistungsstarken und weit verbreiteten Technik in der Positionsbestimmung mittels des Global Navigation Satellite System (GNSS) in geodätischen/wissenschaftlichen und zivilen/täglichen Anwendungen. Ein wichtiges Grundprinzip der GNSS-Datenverarbeitung ist das Äquivalenzprinzip der GNSS-Datenverarbeitung, das 2002 erstmals beschrieben wurde. Das Ziel dieser Arbeit ist die Untersuchung von Hochleistungs-PPP-Algorithmen und die Entwicklung von GNSS-Algorithmen unter Anwendung des Äquivalenzprinzips. Der Kern der Untersuchungen und die Beiträge dieser Arbeit lassen sich wie folgt zusammengefassen. Aufbauend auf dem Äquivalenzprinzip und den Äquivalenz-Eigenschaften von nicht-differenzierenden und differenzierenden GNSS-Algorithmen wird in dieser Arbeit zum ersten Mal die spezifische Gleichwertigkeit von nicht-differenzierenden und zeitdifferenzierenden PPP-Algorithmen theoretisch bewiesen. In diesem Zusammenhang beschreiben wir – als Ergänzung zu den Äquivalenz-Eigenschaften der Tripel-Differenzen - eine bis jetzt noch nicht existierende alternative Methode zum Beweis der Äquivalenz von Tripel-Differenzen und undifferenzierten Beobachtungen. Aufbauend auf der oben erwähnten theoretischen Untersuchung wurde ein zeitlich differenzierender PPP-Algorithmus abgeleitet, der auf dem Äquivalenzprinzip beruht und der dazu benutzt werden kann, die Koordinatendifferenz und die mittlere Geschwindigkeit zwischen benachbarten Beobachtungszeitpunkten zu bestimmen. Ein solcher zeitlich differenzierender PPP-Algorithmus ist in der Lage, sowohl Position als auch Geschwindigkeit aus Phasen- und Code-Beobachtungen zu liefern. Dieser Algorithmus sollte für Anwendungen wie Fluggravimetrie oder Erdbeben-Überwachung nützlich sein und stellt eine effiziente Methode zur Erkennung von Cycle-Slips dar. Diese Arbeit umfasst auch Analysen des Einflusses der Troposphärischen Signalverzögerung auf das PPP, vor allem im Blick mit Beobachtungen in den Polarregionen oder im Fall niedriger Höhengrenzwinkel (sog. Cut-off-Winkel), wo die Positionsbestimmung sehr stark von der Troposphärischen Signalverzögerung beeinflusst ist. In diesem Zusammenhang wird eine Methodologie zur Minimierung des Troposphäreneinflusses vorgeschlagen. Es werden reale meteorologische Daten verwendet und es wird gezeigt, dass dies zur Verbesserung der Präzision des PPP in antarktischen Regionen von Vorteil ist. Außerdem wird der Effekt der troposphärischen Horizontalgradienten-Korrektur analysiert und es wurde bewiesen, dass diese Methode zu einer deutlichen Verbesserung des PPP im Fall niedriger Cut-off-Winkel und hoher Luftfeuchtigkeit führt. In dieser Arbeit werden PPP-Algorithmen mit A-priori-Nebenbedingungen (sog. Constraint) vorgeschlagen und abgeleitet, um die Effizienz und Präzision des PPP zu verbessern. Die in den PPP-Algorithmen angewandten A-priori-Informationen betreffen die geometrischen und physikalischen Eigenschaften von Beobachtungen, von denen vorab eine bestimmte Genauigkeit bekannt ist. Der Einfluss von verschiedenen A-priori-Nebenbedingungen auf verschiedene Parameter innerhalb der PPP-Lösung wird analysiert und validiert. Diese in den PPP-Algorithmen angewandten A-priori-Bedingungen sind aus Nebenbedingungen für Koordinaten, Empängeruhren-Offsets, Troposphären-Verzögerung und Ambiguities abgeleitet. Die Validierung dieser Algorithmen zeigt eine deutliche Verbesserung bezüglich der Konvergenzzeit und der Genauigkeit in der Positionsbestimmung. Ferner wird die Anwendung verschiedener Constraints unter spezifischen Bedingungen diskutiert unf validiert. In dieser Arbeit wurde ein kombinierter PPP-Algorithmus für Multi-Satellitensysteme vorgeschlagen und abgeleitet, der auf dem genannten Äquivalenzprinzip beruht. Mit einem solchen Algorithmus kann die exponentiell ansteigende Computerlast des traditionellen Multi-GNSS-PPP dahingehend reduziert werden, dass es nur einen einfachen linearen Anstieg gibt, wenn mehr GNSS-Satelliten einbezogen werden. Für den Fall der Kombination von GPS mit dem chinesischen Beidou-System (BDS) wird eine Methode vorgeschlagen, die die Berechnung der Ambiguity-Parameter für das BDS-System durch Beitrag von GPS-Beobachtungen schneller beschleunigt. Diese Methode reduziert die Konvergenzzeit im BDS-PPP deutlich. Außerdem wird im Fall der Kombination von GPS und BDS ein Inter-System-Bias (ISB) abgeleitet. Es wird vorgeschlagen, diesen ISB als A-priori-Nebenbedingung in das PPP bei der Kombination von GPS und BDS einzuführen. Dadurch ergeben sich überlegene Resultate für die Konvergenzzeit in der PPP-Prozessierung und die Positionsgenauigkeit in der Ost-Komponente kann verbessert werden. Im traditionellen kombinierten PPP-Verfahren ist es schwierig, den Beitrag jedes einzelnen Systems zur Kombination durch Konstruktion einer Gesamtlösung adaptiv anzugleichen, was zur Verschlechterung in der Kombinationsgenauigkeit führt. In diesem Zusammenhang wurde ein adaptiv kombinierter PPP-Algorithmus vorgeschlagen und entwickelt, der auf dem Äquivalenzprinzip beruht. Dieser Algorithmus ermöglicht eine einfache adaptive Ausgleichung der relativen Wichtungen für jedes Satelliten-System in der Multi-GNSS-Kombination. Durch Nutzung der a-posteriori Kovarianz-Matrix, die für alle gemeinsamen Parameter der einzelnen Satelliten-Systeme aufgestellt wurde und durch die Anwendung der Helmertschen Varianzkomponenten-Schätzung zur adaptiven Ausgleichung der relativen Wichtungen der einzelnen Systeme kann die Genauigkeit der Kombination im Vergleich zum PPP mit identischen Relativgewichten deutlich gesteigert werden. Die entwickelten Algorithmen sind über das Internet anwendbar und könnten für Cloud-Berechnungen im Rahmen eines Internet-GNSS-Dienstes verwendet werden, was für mögliche kommerzielle Anwendungen von Bedeutung sein könnte

    Software-Defined Radio Technologies forGNSS Receivers: A Tutorial Approach to a SimpleDesign and Implementation

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    The field of satellite navigation has witnessed the advent of a number of new systems and technologies: after the landmark design and development of the Global Positioning System (GPS), a number of new independent Global Navigation Satellite Systems (GNSSs) were or are being developed all over the world: Russia's GLONASS, Europe's GALILEO, and China's BEIDOU-2, to mention a few. In this ever-changing context, the availability of reliable and flexible receivers is becoming a priority for a host of applications, including research, commercial, civil, and military. Flexible means here both easily upgradeable for future needs and/or on-the-fly reprogrammable to adapt to different signal formats. An effective approach to meet these design goals is the software-defined radio (SDR) paradigm. In the last few years, the availability of new processors with high computational power enabled the development of (fully) software receivers whose performance is comparable to or better than that of conventional hardware devices, while providing all the advantages of a flexible and fully configurable architecture. The aim of this tutorial paper is surveying the issue of the general architecture and design rules of a GNSS software receiver, through a comprehensive discussion of some techniques and algorithms, typically applied in simple PC-based receiver implementations

    Post-Processing Precise Point Positioning Solutions with Parameter Optimization

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    Precise Point Positioning (PPP) technique can offer position solutions with centimeter-level accuracy by fusing precise satellite orbits and clocks with un-differenced, dual-frequency, pseudo-range, and carrier-phase observables. PPP presents a compelling alternative to Differential Global Positioning Systems, with the benefit that it only requires a single receiver and does not require simultaneous observations from many stations, making it appealing for ongoing research on hydro-graphic survey applications. The National Oceanic and Atmospheric Administration has been working on a buoy system tracked with a Global Positioning Systems receiver and Inertial Measurement Unit sensor using the PPP technique. In the interest of obtaining accurate measurements, this data is post-processed using a software package for position navigation with tight Inertial Navigation System capabilities developed by the Jet Propulsion Laboratory, this is GNSS Inferred Positioning Systems (GIPSYx). GIPSYx Software allows finely controllable user inputs for selectable models and configurations. This flexibility allows fitting the right models for different data sources but requires a tuning process to find suitable configurations. A processing strategy for buoy data with GIPSYx positioning software is described and a method to assess solutions to automatically optimize the process of finding these manually tuned model parameters is provided. Other data sources are considered to generalize this method and prove the concept of optimizing positioning software configurations from output solution evaluation using black-box optimization

    Robust Positioning in the Presence of Multipath and NLOS GNSS Signals

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    GNSS signals can be blocked and reflected by nearby objects, such as buildings, walls, and vehicles. They can also be reflected by the ground and by water. These effects are the dominant source of GNSS positioning errors in dense urban environments, though they can have an impact almost anywhere. Non- line-of-sight (NLOS) reception occurs when the direct path from the transmitter to the receiver is blocked and signals are received only via a reflected path. Multipath interference occurs, as the name suggests, when a signal is received via multiple paths. This can be via the direct path and one or more reflected paths, or it can be via multiple reflected paths. As their error characteristics are different, NLOS and multipath interference typically require different mitigation techniques, though some techniques are applicable to both. Antenna design and advanced receiver signal processing techniques can substantially reduce multipath errors. Unless an antenna array is used, NLOS reception has to be detected using the receiver's ranging and carrier-power-to-noise-density ratio (C/N0) measurements and mitigated within the positioning algorithm. Some NLOS mitigation techniques can also be used to combat severe multipath interference. Multipath interference, but not NLOS reception, can also be mitigated by comparing or combining code and carrier measurements, comparing ranging and C/N0 measurements from signals on different frequencies, and analyzing the time evolution of the ranging and C/N0 measurements

    Improving performance of pedestrian positioning by using vehicular communication signals

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    Pedestrian-to-vehicle communications, where pedestrian devices transmit their position information to nearby vehicles to indicate their presence, help to reduce pedestrian accidents. Satellite-based systems are widely used for pedestrian positioning, but have much degraded performance in urban canyon, where satellite signals are often obstructed by roadside buildings. In this paper, we propose a pedestrian positioning method, which leverages vehicular communication signals and uses vehicles as anchors. The performance of pedestrian positioning is improved from three aspects: (i) Channel state information instead of RSSI is used to estimate pedestrian-vehicle distance with higher precision. (ii) Only signals with line-of-sight path are used, and the property of distance error is considered. (iii) Fast mobility of vehicles is used to get diverse measurements, and Kalman filter is applied to smooth positioning results. Extensive evaluations, via trace-based simulation, confirm that (i) Fixing rate of positions can be much improved. (ii) Horizontal positioning error can be greatly reduced, nearly by one order compared with off-the-shelf receivers, by almost half compared with RSSI-based method, and can be reduced further to about 80cm when vehicle transmission period is 100ms and Kalman filter is applied. Generally, positioning performance increases with the number of available vehicles and their transmission frequency
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