Towards a plug&play solution for real-time precise positioning on mass-market devices

Despite pedestrian and vehicle navigation are the key applications enabled by the development of GNSS technology, the best approach to obtain accurate, reliable, continuous and robust PVT (Position-Velocity-Timing) solutions for this purpose has yet to be identified. The real limiting factor is the environment in which the users usually navigate: e.g. multipath effects and cycle slips in harsh urban environments strongly affect, respectively, pseudorange measurements and the continuity of carrier-phase observations. Therefore, positioning services relying on code-based algorithms cannot always meet the required accuracy - which varies depending on the targeted use case -; on the other hand, phase-based approaches as Real-Time Kinematic (RTK) and Precise Point Positioning (PPP) require strong effort to deal with the ambiguity term and its reinitialization when cycle slips occur. These problems are amplified when GNSS measurements from Android smartphone are considered due to the low-cost, linearly polarized and multi-purpose antenna which inevitably impacts on the quality of GNSS observables. This paper focuses on the performance analysis of GNSS POWER - an algorithm based on the loosely coupling between Single Point Positioning (SPP) solutions and variometric velocity - combined with IGS SSR corrections to increase the accuracy achievable in a real-time stand-alone solution. The integration of SSR corrections within GNSS POWER algorithm is validated in both static and kinematic scenarios using high-end GNSS receivers and Andorid smartphones. The results demonstrated the advantages of using SSR corrections on SPP and GNSS POWER solutions also on Android devices opening to new applications of real-time stand-alone positioning approaches on mass-market devices

센티미터 급 광역 보강항법 시스템의 반송파 위상 기반 보정정보 생성 알고리즘에 관한 연구

학위논문(박사)--서울대학교 대학원 :공과대학 기계항공공학부,2020. 2. 기창돈.Recently, the demand for high-precision navigation systems for centimeter-level service has been growing rapidly for various Global Navigation Satellite System (GNSS) applications. The network Real-Time Kinematic (RTK) is one of the candidate solution to provide high-accuracy position to user in real-time. However, the network RTK requires a lot of reference stations for nationwide service. Furthermore, it requires high-speed data-link for broadcasting their scalar-type corrections. This dissertation proposed a new concept of satellite augmentation system called Compact Wide-Area RTK, which provides centimeter-level positioning service on national or continental scales to overcoming the limitation of the legacy network RTK methods. Using the wide-area network of multiple reference stations whose distance is 200~1,000 km, the proposed system generates three types of carrier-phase-based corrections: satellite orbit corrections, satellite code/phase clock (CPC) corrections, tropospheric corrections. Through the strategy of separating the scalar-type corrections of network RTK into vector forms of each error component, it is enable to expand network RTK coverage to continental scale using a similar number of reference stations as legacy meter-level Satellite-Based Augmentation System (SBAS). Furthermore, it is possible to broadcast their corrections over a wide-area using geosynchronous (GEO) satellite with extremely low-speed datalink of 250 bps likewise of legacy SBAS. To sum up, the proposed system can improve position accuracy by centimeter-level while maintaining the hardware infrastructure of the meter-level legacy SBAS. This study mainly discussed on the overall system architecture and core algorithms for generating satellite CPC corrections and tropospheric corrections. This study proposed a new Three-Carrier Ambiguity Resolution (TCAR) algorithm using ionosphere-free combinations to correctly solve the integer ambiguity in wide-area without any ionospheric corrections. The satellite CPC corrections are calculated based on multiple stations for superior and robust performance under communication delay and outage. The proposed algorithm dramatically reduced the latency compensation errors and message amounts with compare to conventional RTK protocols. The tropospheric corrections of the compact wide-area RTK system are computed using GPS-estimated precise tropospheric delay and weather data based model together. The proposed algorithm adopts spherical harmonics function to significantly reduce the message amounts and required number of GPS reference stations than the network RTK and Precise Point Positioning-RTK (PPP-RTK), while accurately modeling the spatial characteristic of tropospheric delay with weather data together. In order to evaluate the user domain performance of the compact wide-area RTK system, this study conducted the feasibility test on mid-west and south USA using actual GPS measurements. As a result, the 95% horizontal position error is about 1.9 cm and the 95% vertical position error is 7.0 cm after the integer ambiguity is correctly fixed using GPS-only signals. The user ambiguity resolution takes about 2 minutes, and success-fix rate is about 100 % when stable tropospheric condition. In conclusion, the compact wide-area RTK system can provide centimeter-level positioning service to wide-area coverage with extremely low-speed data link via GEO satellite. We hope that this new system will consider as candidate solution for nationwide centimeter-level service such as satellite augmentation system of the Korea Positioning System (KPS).최근 자율주행자동차, 무인 드론 배송, 충돌 회피, 무인트랙터를 이용한 스마트 무인 경작 등 위성항법시스템(GNSS, Global Navigation Satellite System)을 사용하는 다양한 응용분야에서 수 cm 수준의 정밀 위치 정보에 대한 요구가 급격히 증가하고 있다. 본 학위논문에서는 1 m 급의 정확하고 신뢰성 높은 위치 서비스를 제공하는 기존의 정지궤도위성 기반 광역 보강항법 시스템(SBAS, Satellite-Based Augmentation System)의 기준국 인프라를 유지하면서 항법 성능을 수 cm 수준으로 향상시키기 위해 반송파 위상 기반의 초정밀 보정정보 생성 알고리즘에 관한 연구를 수행하였다. 실시간 정밀 측위(RTK, Real-Time Kinematic)는 반송파 위상 측정치에 포함된 미지정수를 정확하게 결정하여 수 cm 수준의 정밀 항법 서비스를 가능하게 하는 대표적인 기법이다. 그 중에서도 약 50~70 km 간격으로 분포된 다수의 기준국 정보를 활용하는 Network RTK 기법은 동적 사용자의 빠르고 정확한 위치 결정이 가능한 인프라로서 주목받고 있다. 하지만 스칼라 형태로 구성된 Network RTK 보정정보는 각 기준국 별로 관측된 위성 수에 따라 생성이 되기 때문에 보정 데이터 량이 상당히 방대하다. 메시지 전송에 필요한 데이터 량이 많을수록 고속의 통신 환경을 필요로 하며, 메시지 시간 지연이나 통신 단절에 매우 취약한 문제를 가지고 있다. 또한 스칼라 형태의 보정정보는 사용자와 기준국 간의 거리가 멀어질수록 보정 오차가 크게 발생하기 때문에 대륙 혹은 나라 규모의 광역에서 서비스하기 위해서는 수십~수백 개 이상의 기준국 인프라 구축이 필수적이다. 예를 들어, SBAS가 한반도 지역 서비스를 위해 5~7개의 기준국이 필요한 반면 Network RTK는 90~100개의 기준국이 필요하다. 즉 Network RTK는 시스템 구축 및 유지 비용이 SBAS 대비 약 15배 정도 많이 들게 된다. 본 논문에서는 기존 Network RTK의 문제점을 해결하기 위한 방법으로 대륙 급 광범위한 영역에서 실시간으로 cm급 초정밀 위치결정 서비스 제공이 가능한 Compact Wide-Area RTK 라는 새로운 개념의 광역보강항법시스템 아키텍처를 제안하였다. Compact Wide-Area RTK는 약 200~1,000 km 간격으로 넓게 분포된 기준국 네트워크를 활용하여 반송파 위상 기반의 정밀한 위성 궤도 보정정보, 위성 Code/Phase 시계 보정정보, 대류층 보정정보를 생성하는 시스템이다. 기존 스칼라 형태의 Network RTK 보정정보 대신 오차 요소 별 벡터 형태의 정밀 보정정보를 생성함으로써 데이터 량을 획기적으로 절감하고 서비스 영역을 확장할 수 있다. 최종적으로 SBAS와 마찬가지로 250 bps의 저속 통신 링크를 가진 정지궤도위성을 통해 광역으로 보정정보 방송이 가능하다. 본 논문에서는 3가지 보정정보 중 위성 Code/Phase 시계 보정정보와 대류층 보정정보 생성을 위한 핵심 알고리즘에 대해 중점적으로 연구하였다. 반송파 위상 기반의 정밀 보정정보 생성을 위해서는 먼저 미지정수를 정확하게 결정해야 한다. 본 논문에서는 삼중 주파수 반송파 위상 측정치의 무-전리층 조합을 활용하여 전리층 보정정보 없이도 정확하게 미지정수 결정 가능한 새로운 방법을 제안하였다. 위성 Code/Phase 시계 보정정보는 통신 지연 및 고장 시 우수하고 강건한 성능을 위해 다중 기준국의 모든 측정치를 활용하여 추정된다. 이 때 각 기준국 별 서로 다른 미지정수 때문에 발생하는 문제는 앞서 정확하게 결정된 기준국 간 이중차분 된 미지정수를 활용하여 수준을 조정하는 과정을 통해 해결이 가능하다. 그 결과 생성된 위성 Code/Phase 보정정보 메시지의 크기, 변화율, 잡음 수준이 크게 개선되었고, 통신 지연 시 오차 보상 성능이 기존 RTK 프로토콜 보다 99% 향상 됨을 확인하였다. 대류층 보정정보는 적은 수의 기준국 만을 활용하여 정확하게 대류층을 모델링하기 위해 자동 기상관측시스템으로부터 수집한 기상 정보를 추가로 활용하여 생성된다. 본 논문에서는 GNSS 기준국 네트워크로부터 정밀하게 추정된 반송파 위상 기반 수직 대류층 지연과 기상정보 기반으로 모델링 된 수직 대류층 지연을 함께 활용할 수 있는 새로운 알고리즘을 제안하였다. 구면조화함수를 사용하여 Network RTK 및 PPP-RTK 보다 필요한 메시지 양과 기준국 수를 크게 감소시키면서도 RMS 2 cm 수준으로 정확한 보정정보 생성이 가능함을 확인하였다. 본 논문에서 제안한 Compact Wide-Area RTK 시스템의 항법 성능을 검증하기 위해 미국 동부 지역 6개 기준국의 실측 GPS 데이터를 활용하여 테스트를 수행하였다. 그 결과 제안한 시스템은 미지정수 결정 이후 사용자의 95% 수평 위치 오차 1.9 cm, 95% 수직 위치 오차 7.0 cm 로 위치를 정확하게 결정하였다. 사용자 미지정수 결정 성능은 대류층 안정 상태에서 약 2분 내로 100% 의 성공률을 가진다. 본 논문에서 제안한 시스템이 향후 한국형 위성항법 시스템(KPS, Korean Positioning System)의 전국 단위 센티미터 급 서비스를 위한 알고리즘으로 활용되기를 기대한다.CHAPTER 1. Introduction 1 1.1 Motivation and Purpose 1 1.2 Former Research 4 1.3 Outline of the Dissertation 7 1.4 Contributions 8 CHAPTER 2. Overview of GNSS Augmentation System 11 2.1 GNSS Measurements 11 2.2 GNSS Error Sources 14 2.2.1 Traditional GNSS Error Sources 14 2.2.2 Special GNSS Error Sources 21 2.2.3 Summary 28 2.3 GNSS Augmentation System 29 2.3.1 Satellite-Based Augmentation System (SBAS) 29 2.3.2 Real-Time Kinematic (RTK) 32 2.3.3 Precise Point Positioning (PPP) 36 2.3.4 Summary 40 CHAPTER 3. Compact Wide-Area RTK System Architecture 43 3.1 Compact Wide-Area RTK Architecture 43 3.1.1 WARTK Reference Station (WRS) 48 3.1.2 WARTK Processing Facility (WPF) 51 3.1.3 WARTK User 58 3.2 Ambiguity Resolution and Validation Algorithms of Compact Wide-Area RTK System 59 3.2.1 Basic Theory of Ambiguity Resolution and Validation 60 3.2.2 A New Ambiguity Resolution Algorithms for Multi-Frequency Signals 65 3.2.3 Extra-Wide-Lane (EWL) Ambiguity Resolution 69 3.2.4 Wide-Lane (WL) Ambiguity Resolution 71 3.2.5 Narrow-Lane (NL) Ambiguity Resolution 78 3.3 Compact Wide-Area RTK Corrections 83 3.3.1 Satellite Orbit Corrections 86 3.3.2 Satellite Code/Phase Clock (CPC) Corrections 88 3.3.3 Tropospheric Corrections 89 3.3.4 Message Design for GEO Broadcasting 90 CHAPTER 4. Code/Phase Clock (CPC) Correction Generation Algorithm 93 4.1 Former Research of RTK Correction Protocol 93 4.1.1 Observation Based RTK Data Protocol 93 4.1.2 Correction Based RTK Data Protocol 95 4.1.3 Compact RTK Protocol 96 4.2 Satellite CPC Correction Generation Algorithm 100 4.2.1 Temporal Decorrelation Error Reduced Methods 102 4.2.2 Ambiguity Level Adjustment 105 4.2.3 Receiver Clock Synchronization 107 4.2.4 Averaging Filter of Satellite CPC Correction 108 4.2.5 Ambiguity Re-Initialization and Message Generation 109 4.3 Correction Performance Analysis Results 111 4.3.1 Feasibility Test Environments 111 4.3.2 Comparison of RTK Correction Protocol 113 4.3.3 Latency Compensation Performance Analysis 116 4.3.4 Message Data Bandwidth Analysis 119 CHAPTER 5. Tropospheric Correction Generation Algorithm 123 5.1 Former Research of Tropospheric Correction 123 5.1.1 Tropospheric Corrections for SBAS 124 5.1.2 Tropospheric Corrections of Network RTK 126 5.1.3 Tropospheric Corrections of PPP-RTK 130 5.2 Tropospheric Correction Generation Algorithm 136 5.2.1 ZWD Estimation Using Carrier-Phase Observations 138 5.2.2 ZWD Measurements Using Weather Data 142 5.2.3 Correction Generation Using Spherical Harmonics 149 5.2.4 Correction Applying Method for User 157 5.3 Correction Performance Analysis Results 159 5.3.1 Feasibility Test Environments 159 5.3.2 Zenith Correction Domain Analysis 161 5.3.3 Message Data Bandwidth Analysis 168 CHAPTER 6. Compact Wide-Area RTK User Test Results 169 6.1 Compact Wide-Area RTK User Process 169 6.2 User Performance Test Results 173 6.2.1 Feasibility Test Environments 173 6.2.2 User Range Domain Analysis 176 6.2.3 User Ambiguity Domain Analysis 182 6.2.4 User Position Domain Analysis 184 CHAPTER 7. Conclusions 189 Bibliography 193 초 록 207Docto

Zur GNSS-basierten Bestimmung von Position und Geschwindigkeit in der Fluggravimetrie

Das weltumspannende Satelliten-Navigationssystem GNSS spielt eine wichtige Rolle für die Fluggravimetrie. Gegenstand dieser Arbeit ist die Entwicklung zuverlässiger GNSS-Algorithmen und Software für die hochgenaue GNSS-Datenanalyse in der Fluggravimetrie. Ausgehend von den Anforderungen für praktische Anwendungen der Fluggravimetrie lassen sich die Beiträge und Schwerpunkte dieser Dissertation wie folgt zusammenfassen: Ausgleichs- bzw. Schätzungs-Algorithmen: Ausgehend von den Genauigkeitsanforderungen an die GNSS-basierte Positionsbestimmung in der Fluggravimetrie werden in einer kinematischen GNSS-Daten-Auswertung eine Schätzung nach kleinsten Quadraten einschließlich der Eliminierung von Störparametern sowie ein Zwei-Wege-Kalman-Filter angewendet. Das Ziel der beiden Ausgleichsverfahren ist es, an jedem Messzeitpunkt zunächst globale Parameter (wie System-Fehler und Trägerwellen-Ambiguities) und anschließend lokale Parameter (wie Position und Geschwindigkeit der bewegten Messplattform) zu bestimmen. Die angewandten Methoden sind sehr effizient und ergeben hochpräzise Resultate für die GNSS-Datenanalyse. Analyse von Genauigkeit und Zuverlässigkeit: Die Genauigkeit und Zuverlässigkeit der Resultate der präzisen kinematischen GNSS-Positionsbestimmung werden untersucht. Dabei wird eine besondere Methode zur Bewertung der Genauigkeit der kinematischen GNSS-Positionsbestimmung vorgeschlagen, wo bekannte Entfernungen zwischen mehreren GNSS-Antennen als Genauigkeits-Maßstab genommen werden. Weiterhin wird der Einfluss der Uhrenfehler der GNSS-Empfänger auf die Genauigkeit der kinematischen Positionsbestimmung für die Hochgeschwindigkeits-Plattform untersucht. Für dabei auftretende Probleme wird eine Lösung vorgeschlagen. Algorithmen der kinematischen Positionsbestimmung die auf mehreren Referenzstationen beruhen: Um das Problem der im Falle langer Basislinien abnehmenden Genauigkeit in der relativen kinematischen GNSS-Positionsbestimmung zu bewältigen, wird ein neuer Algorithmus vorgeschlagen. Er beruht auf der apriori Einführung von Exzentrizitäts-Bedingungen für mehrere Referenzstationen. Dieser Algorithmus erhöht die Genauigkeit und Zuverlässigkeit der Ergebnise in der kinematischen Positionsbestimmung für große Regionen resp. lange Basislinien. Präzise GNSS-Positionsbestimmung, beruhend auf robuster Schätzung: Das Vorhandensein von groben Fehlern in den GNSS-Beobachtungen verursacht das Auftreten von Ausreißern in den Ergebnissen der Positionsbestimmung. Um dieses Problem zu überwinden, wird ein robuster Ausgleichungs-Algorithmus angewendet, der die Auswirkungen von gro-ben Fehlern in den Ergebnissen der kinematischen GNSS-Positionsbestimmung beseitigt. Kinematische Positionierung auf der Basis mehrerer bewegter Stationen: In der Fluggravimetrie werden in der Regel mehrere GNSS-Antennen auf einer bewegten Plattform installiert. In diesem Zusammenhang wird deshalb erstens ein kinematisches GNSS-Positionsbestimmungsverfahren vorgeschlagen, das auf mehreren gleichzeitig bewegten GNSS-Stationen basiert. Aus den bekannten, konstanten Distanzen zwischen den GNSS-Antennen werden dabei apriori Exzentrizitäts-Bedingungen abgeleitet und in die Positions-schätzung eingeführt. Dies verbessert die Zuverlässigkeit des Messsystems. Zweitens wird solch ein Ansatz auch zur Bestimmung eines gemeinsamen Refraktionsparameters aller GNSS-Antennen der Plattform für den feuchten Teil der Atmosphäre verwendet. Dieses Verfahren reduziert nicht nur die Menge der geschätzten Parameter, sondern verringert auch die Korrelation zwischen den atmosphärischen Parametern. Kinematische Positionierung basierend auf der Kombination verschiedener GNSS-Systeme: Um die Zuverlässigkeit und Genauigkeit der kinematischen Positionsbestimmung zu verbessern, werden die Signale mehrerer GNSS-Systeme (d.h. GPS und GLONASS) gemeinsam registriert und ausgewertet (sog. GNSS-Integration). Zur Optimierung des relativen Gewichts zwischen den Daten der verschiedenen GNSS-Systeme wird die Helmertsche Varianz-Komponenten-Schätzung angewandt. Der auf dieser Basis entwickelte Kombinationsalgorithmus ermöglicht die Verbesserung der Beiträge von mehreren GNSS-Systemen. Geschwindigkeitsbestimmung mit GNSS-Doppler-Daten: Die Auswertung der Schwere-Messdaten in der Fluggravimetrie verlangt die hochgenaue Bestimmung des Geschwindigkeitsvektors der bewegten Plattform. Deshalb werden rohe GNSS-Doppler-Beobachtungen verwendet, um die Geschwindigkeit der bewegten Plattform im Falle hoch-dynamischer Flugbedingungen kinematisch zu bestimmen. Darüberhinaus werden aus der Trägerphase abgeleitete Doppler-Beobachtungen verwendet, um präzise Geschwindigkeitsschätzungen im Falle weniger dynamischer Flugbedingungen zu erhalten. Die Kombination verschiedener GNSS-Systeme wird auch bei der Doppler-Geschwindigkeitsbestimmung angewandt. Hierzu wird die Anwendung der Helmertschen Varianzkomponenten-Schätzung und einer robusten Schätzung untersucht. Software Entwicklung und Anwendung: Um die aktuellen Anforderungen der GNSS-basierten Positionsbestimmung in der Flug- sowie Schiffsgravimetrie zu erfüllen, wurde ein Software-System (HALO_GNSS) für die präzise kinematische GNSS-Flugbahn- und Geschwindigkeitsberechnung kinematischer Plattformen entwickelt. Die in dieser Arbeit vorgeschlagenen Algorithmen wurden in diese Software integriert. Um die Effizienz der vorgeschlagenen Algorithmen und der HALO_GNSS Software zu prüfen, wurde diese Software sowohl in Flug- als auch in Schiffsgravimetrie-Projekten des GFZ Potsdam angewandt. Alle Ergebnisse werden verglichen und geprüft und es wird gezeigt, dass die angewandten Methoden die Zuverlässigkeit und Genauigkeit der kinematischen Positions- und Geschwindigkeitsbestimmung effektiv verbessern. Die Verwendung der Software HA-LO_GNSS ermöglicht kinematische Positionsbestimmung mit einer Genauigkeit von 1-2 cm sowie Geschwindigkeitsbestimmung mit einer Genauigkeit von ca. 1 cm/s mit Roh- und etwa 1 mm/s mit aus der Trägerphase abgeleiteten Doppler-Beobachtungen.The Global Navigation Satellite System (GNSS) plays a significant role in the fields of airborne gravimetry. The objective of this thesis is to develop reliable GNSS algorithms and software for kinematic highly precise GNSS data analysis in airborne gravimetry. Based on the requirements for practical applications in airborne gravimetry and shipborne gravimetry projects, the core research and the contributions of this thesis are summarized as follows: Estimation Algorithm: Based on the accuracy requirements for GNSS precise positioning in airborne gravimetry, the estimation algorithms of least squares including the elimination of nuisance parameters as well as a two-way Kalman filter are applied to the kinematic GNSS data post-processing. The goal of these adjustment methods is to calculate non-epoch parameters (such as system error estimates or carrier phase ambiguity parameters) using all data in the first step, followed by the calculation of epoch parameters (such as position and velocity parameters of the kinematic platform) at every epoch. These methods are highly efficient when dealing with massive amounts of data, and give the highly precise results for the GNSS data analyzed. Accuracy Evaluation and Reliability Analysis: The accuracy evaluation and reliability analysis of the results from precise kinematic GNSS positioning is studied. A special accuracy evaluation method in GNSS kinematic positioning is proposed, where the known distances among multiple antennas of GNSS receivers are taken as an accuracy evaluation index. The effect of the GNSS receiver clock error in the accuracy evaluation for GNSS kinematic positioning results of a high-speed motion platform is studied and a solution is proposed. Kinematic Positioning Based on Multiple Reference Stations Algorithms: In order to overcome the problem of decreasing accuracy in GNSS relative kinematic positioning for long baselines, a new relative kinematic positioning method based on a priori constraints for multiple reference stations is proposed. This algorithm increases the accuracy and reliability of kinematic positioning results for large regions resp. long baselines. GNSS Precise Positioning Based on Robust Estimation: In order to solve the problem of outliers occurring in positioning results which are caused by the presence of gross errors in the GNSS observations, a robust estimation algorithm is applied to eliminate the effects of gross errors in the results of GNSS kinematic precise positioning. Kinematic Positioning Based on Multiple Kinematic Stations: In airborne gravimetry, multiple antennas of GNSS receivers are usually mounted on the kinematic platform. Firstly, a GNSS kinematic positioning method based on multiple kinematic stations is proposed. Using the known constant distances among the multiple GNSS antennas, a kinematic positioning method based on a priori distance constraints is proposed to improve the reliability of the system. Secondly, such an approach is also used for the estimation of a common atmospheric wet delay parameter among the multiple GNSS antennas mounted on the platform. This method does not only reduce the amount of estimated parameters, but also decreases the correlation among the atmospheric parameters. Kinematic Positioning Based on GNSS Integration: To improve the reliability and accuracy of kinematic positioning, a kinematic positioning method using multiple GNSS systems integration is addressed. Furthermore, a GNSS integration algorithm based on Helmert’s variance components estimation is proposed to adjust the weights in a reasonable way. This improves the results when combining data of the different GNSS systems. Velocity Determination Using GNSS Doppler Data: Airborne gravimetry requires instantaneous velocity results, thus raw Doppler observations are used to determine the kinematic instantaneous velocity in high-dynamic environments. Furthermore, carrier phase derived Doppler observations are used to obtain precise velocity estimates in low-dynamic environments. Then a method of Doppler velocity determination based on GNSS integration with Helmert’s variance components estimation and robust estimation is studied. Software Development and Application: In order to fulfill the actual requirements of airborne as well as shipborne gravimetry on GNSS precise positioning, a software system (HALO_GNSS) for precise kinematic GNSS trajectory and velocity determination for kinematic platforms has been developed. In this software, the algorithms as proposed in this thesis were adopted and applied. In order to evaluate the effectiveness of the proposed algorithm and the HALO_GNSS software, this software is applied in airborne as well as shipborne gravimetry projects of GFZ Potsdam. All results are compared and examined, and it is shown that the applied approaches can effectively improve the reliability and accuracy of the kinematic position and velocity determination. It allows the kinematic positioning with an accuracy of 1-2 cm and the velocity determination with an accuracy of approximately 1 cm/s using raw and approximately 1 mm/s using carrier phase derived Doppler observations

Forward and Inverse Modeling of GPS Multipath for Snow Monitoring

Snowpacks provide reservoirs of freshwater, storing solid precipitation and delaying runoff to be released later in the spring and summer when it is most needed. The goal of this dissertation is to develop the technique of GPS multipath reflectometry (GPS-MR) for ground-based measurement of snow depth. The phenomenon of multipath in GPS constitutes the reception of reflected signals in conjunction with the direct signal from a satellite. As these coherent direct and reflected signals go in and out of phase, signal-to-noise ratio (SNR) exhibits peaks and troughs that can be related to land surface characteristics. In contrast to other GPS reflectometry modes, in GPS-MR the poorly separated composite signal is collected utilizing a single antenna and correlated against a single replica. SNR observations derived from the newer L2-frequency civilian GPS signal (L2C) are used, as recorded by commercial off-the-shelf receivers and geodetic-quality antennas in existing GPS sites. I developed a forward/inverse approach for modeling GPS multipath present in SNR observations. The model here is unique in that it capitalizes on known information about the antenna response and the physics of surface scattering to aid in retrieving the unknown snow conditions in the antenna surroundings. This physically-based forward model is utilized to simulate the surface and antenna coupling. The statistically-rigorous inverse model is considered in two parts. Part I (theory) explains how the snow characteristics are parameterized; the observation/parameter sensitivity; inversion errors; and parameter uncertainty, which serves to indicate the sensing footprint where the reflection originates. Part II (practice) applies the multipath model to SNR observations and validates the resulting GPS retrievals against independent in situ measurements during a 1-3 year period in three different environments - grasslands, alpine, and forested. The assessment yields a correlation of 0.98 and an RMS error of 6-8 cm, with the GPS under-estimating in situ snow depth by approximately 15%. GPS daily site averages were found effective in mitigating random noise without unduly smoothing the sharp transitions as captured in new snow events. This work corroborates the readiness of quality-controlled GPS-MR for snow depth monitoring, reinforcing its maturity for operational usage

PoCoLoCo : Positioning through cooperating loquacious communications

Aerial Transportation system is based in a legacy infrastructure that supports its different functionality separately. There is a tendency to simplify the infrastructure, increasing its efficiency, technical and monetary. UAS are perceived by the general public as simplified versions of the conventional aviation because they have not any human flight crew on board. In fact, they have a flight crew, but this flight crew is placed on ground adding some complications to the system (e.g: Command & Control link). Conventional aviation perceives UAS as a source of problems, mainly because they have no human flight crew on board capable of creating the situational awareness of the UAS. This lack of situational awareness compromises as well the rest of airspace users safety. This PhD explores the capability of UAS to contribute to the situational awareness of both the own aircraft (generating navigation data) as to the situational awareness of the rest of airspace users (generating surveillance data). The contribution to the situational awareness of both the own aircraft (navigation data) as well as the rest of airspace users (surveillance) is simulated assuming UAS communications based on TDMA and at the communication rates described in the literature. The simulation scenario has been kept simple with a low communication rate and a low number of UAS flying in the simulated area. The results of navigation are in line with the RNP1. The results in surveillance are in line with the 3NM separation but with a refresh rate much higher. Then, with this proposal, UAS could be considered as contributors to the situational awareness instead as the problem that destroys the situational awareness.El sistema de transport aeri es basa en una infraestructura que implementa les seves funcionalitats per separat. Hi ha una tendència a simplificar la infraestructura, augmentant la seva eficiència, tècnica i monetària. Els UAS són percebuts pel públic en general com versions simplificades de l'aviació convencional, ja que no tenen cap tripulació humana a bord. De fet, tenen una tripulació de vol, però la tripulació de vol es a terra, afegint algunes complicacions en el sistema (per exemple: enllaç de comandament i control). L'aviació convencional percep els UAS com una font de problemes, sobretot perquè l'absencia de tripulació de vol humana a bord capaç de crear la consciència situacional de l'UAS. Aquesta manca de consciència situacional, compromet doncs la seguretat dels usuaris de l'espai aeri. Aquesta PhD explora la capacitat dels UAS per contribuir a la consciència situacional tant de la pròpia aeronau (generació de dades de navegació) com a la consciència situacional de la resta dels usuaris de l'espai aeri (generació de dades de vigilància). La contribució a la consciència situacional tant de la pròpia aeronau (dades de navegació), com de la resta d'usuaris de l'espai aeri (vigilància) es simula assumint comunicacions UAS basats en TDMA amb uns ratis de comunicació descrits a la literatura. L'escenari de simulació s'ha mantingut simple amb una taxa de comunicació baixa i un baix nombre d'UAS volan a la zona simulada. Els resultats de la navegació estan en línia amb la RNP1. Els resultats de la vigilància estan en línia amb la separació 3nm però amb una freqüència d'actualització molt més alt que l'oferta pels radars. Com a conclusió, aquesta proposta considera els UAS com a contribuents a la consciència situacional en lloc de com un problema que destrueix la consciència situacional

Sequential Importance Resampling Particle Filter for Ambiguity Resolution

In this thesis the sequential importance resampling particle filter for estimating the full geometry-based float solution state vector for Global Navigation Satellite System (GNSS) ambiguity resolution is implemented. The full geometry-based state vector, consisting on position, velocity, acceleration, and float ambiguities, is estimated using a particle filter in RTK mode. In contrast to utilizing multi-frequency and multi-constellation GNSS measurements, this study employed solely L1 GPS code and carrier phase observations. This approach simulates scenarios wherein the signal reception environment is suboptimal and only a restricted number of satellites are visible. However, it should be noted that the methodology outlined in this thesis can be expanded for cases involving multiple frequencies and constellations. The distribution of particles after the resampling step is used to compute an empirical covariance matrix Pk based on the incorporated observations at each epoch. This covariance matrix is then used to transform the distribution using the decorrelating Z transformation of the LAMBDA method [1]. The performance of a float solution based on point mass representation is compared to the typically used extended Kalman filter (EKF) for searching the integer ambiguities using the three common search methods described in [2]: Integer Rounding, Integer Bootstrapping, and Integer Least Squares with and without the Z transformation. As Bayesian estimators are able to include highly non-linear elements and accurately describe non-Gaussian posterior densities, the particle filter outperforms the EKF when a constraint leading to highly non-Gaussian distributions is added to the estimator. Such is the case of the map-aiding constraint, which integrates digital road maps with GPS observations to compute a more accurate position state. The comparison between the position accuracy of the particle filter solution with and without the map-aiding constraint to the solution estimated with the EKF is made. The algorithm is tested in different segments of data and shows how the position convergence improves when adding digital road map information within the first thirty seconds of initializing the Particle Filter in different scenarios that include driving in a straight line, turning, and changing lanes. The assessment of the effect of the map-aiding algorithm on the ambiguity domain is carried out as well and it is shown how the convergence time of the float ambiguities improves when the position accuracy is improved by the constraint. The particle filter is able to weight the measurements according to any kind of distribution, unlike the EKF which always assumes a Gaussian distribution. The performance of the PF when having non-Gaussian measurements is assessed, such as when the measurements are distorted by multipath. Two additional steps are implemented, an outlier detection technique based on the predicted set of particles, and the use of a mixture of Gaussians to weight the measurements detected as outliers. The implemented outlier detection algorithm is based on the residual (or innovation) testing technique which is commonly applied into the EKF. The innovation and its covariance matrix are estimated from a predicted set of residuals using the transitional prior distribution and the measurement model. Then, the innovation is compared against the critical value of N (0, 1) at a level of significance α. The mixture of Gaussians is the weighted sum of two Gaussians, one from the measurement noise matrix, and the second being a scaled version of the first one describing the multipath error. This procedure de-weights the measurements with multipath, and reduces the bias in the position estimate. The proposed map-aiding algorithm improves the ambiguity convergence time by approximately 80%, while the deweighting process enhances it by around 25% for the segments of the vehicle dataset that were analyzed. This work serves as a demonstration of cases wherein the particle filter addresses the limitations of the EKF in estimating the float solution in ambiguity resolution. Such limitations include constraints that give rise to non-Gaussian probability density functions and the utilization of a distinct likelihood function for outlier measurements, as opposed to the Gaussian assumption made by the EKF. The proposed map-aided particle filter can be implemented in real-time to enhance the float ambiguity during the initial epochs after the filter has been initialized. This implementation proves beneficial in urban environments where there is a loss or complete obstruction of the GNSS signal