239 research outputs found

    NLOS GPS signal detection using a dual-polarisation antenna

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    The reception of indirect signals, either in the form of non-line-of-sight (NLOS) reception or multipath interference, is a major cause of GNSS position errors in urban environments. We explore the potential of using dual-polarisation antenna technology for detecting and mitigating the reception of NLOS signals and severe multipath interference. The new technique computes the value of the carrier-power-to-noise-density (C/N0) measurements from left-hand circular polarised outputs subtracted from the right-hand circular polarised C/N0 counterpart. If this quality is negative, NLOS signal reception is assumed. If the C/N0 difference is positive, but falls below a threshold based on its lower bound in an open-sky environment, severe multipath interference is assumed. Results from two experiments are presented. Open-field testing was first performed to characterise the antenna behaviour and determine a suitable multipath detection threshold. The techniques were then tested in a dense urban area. Using the new method, two signals in the urban data were identified as NLOS-only reception during the occupation period at one station, while the majority of the remaining signals present were subject to a mixture of NLOS reception and severe multipath interference. The point positioning results were dramatically improved by excluding the detected NLOS measurements. The new technique is suited to a wide range of static ground applications based on our results

    Implementation of Moving-Base-GNSS en NAVKA Multisensor GNSS / MEMS /optics navigation algorithms and systems

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    [EN] Implementation of Moving-Base-GNSS in NAVKA Multisensor GNSS / MEMS / Optics Navigation Algorithms and Systems. Development and implementation of an ambiguity resolution algorithm related to the Moving-Base-GNSS situation. Algorithm implementation in the RTKLIB open source library (C / C ++). Development of software that allows to calculate the position of a rover from the coordinates of a master receiver (DGNSS / PPP) and from the baselines calculated with the algorithm in question.[ES] Implementation of Moving-Base-GNSS in NAVKA Multisensor GNSS/MEMS/Optics Navigation Algorithms and Systems. Desarrollo e implementación de un algoritmo de resolución de ambigüedades relacionado con la situación Moving-Base-GNSS. Implementación del algoritmo en la librería de código abierto RTKLIB (C/C++). Desarrollo de un software que permite calcular la posición de un rover a partir de las coordenadas de un receptor máster (DGNSS/PPP) y de las líneas base calculadas con el algoritmo en cuestión.Hernández Olcina, J. (2019). Implementation of Moving-Base-GNSS en NAVKA Multisensor GNSS / MEMS /optics navigation algorithms and systems. http://hdl.handle.net/10251/139434TFG

    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

    Precise Real-Time Positioning Using Network RTK

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    GNSS multi-frequency receiver single-satellite measurement validation method

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    A method is presented for real-time validation of GNSS measurements of a single receiver, where data from each satellite are independently processed. A geometry- free observation model is used with a reparameterized form of the unknowns to overcome rank deficiency of the model. The ionosphere error and non-constant biases such as multipath are assumed changing relatively smoothly as a function of time. Data validation and detection of errors are based on statistical testing of the observation residuals using the detection–identification–adaptation approach. The method is applicable to any GNSS with any number of frequencies. The performance of validation method was evaluated using multi-frequency data from three GNSS (GPS, GLONASS, and Galileo) that span 3 days in a test site at Curtin University, Australia. Performance of the method in detection and identification of outliers in code observations, and detection of cycle slips in phase data were examined. Results show that the success rates vary according to precision of observations and their number as well as size of the errors. The method capability is demonstrated when processing four IOV Galileo satellites in a single-point-positioning mode and in another test by comparing its performance with Bernese software in detection of cycle slips in precise point-positioning processing using GPS data

    Diagnostic Tools Using a Multi-Constellation Single-Receiver Single-Satellite Data Validation Method

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    The use of single-receiver single-satellite data validation parameters for numerical and graphical diagnostics of the multi-frequency observations is presented. This method validates Global Navigation Satellite System (GNSS) measurements of a single receiver where data from each satellite are independently processed using a geometry-free observation model with a reparameterised form of the unknowns. The method is applicable to any GNSS with any number of frequencies. The diagnostic tools are based on checking agreement of characteristics of the validation test statistics against theory. The use of these diagnostics in static and kinematic modes is demonstrated using multiple-frequency data from the three GNSS constellations; Global Positioning System (GPS), Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS) and Galileo

    사용자 상황인지 딥러닝을 사용한 GPS 반송파 / 관성 센서 결합 스마트폰 보행자 항법

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    학위논문 (석사)-- 서울대학교 대학원 : 공과대학 기계항공공학부, 2019. 2. 여재익.본 논문에서는 스마트폰 Galaxy S8 환경에서 GPS / INS 결합 보행자 항법을 수행하였으며, 스마트폰 센서의 특성을 자세히 분석하였다. 이에 최근 공개된 Android GNSS API 를 사용하여 GPS 원시데이터를 항법에 이용하면서, Cycle slip 을 보정한 Carrier phase 를 이용한 속도 결정법을 사용하였다. 이로 인해 기존의 NMEA GPS 를 사용한 방식의 스마트폰 보행자 항법보다 정밀한 위치, 속도 항법이 가능하였고, 성능을 향상 시켰다. 또한 사용자 상황 분석이 가능한 분류 딥러닝 기법을 사용하여 각 보행 상황에 따른 분류감지가 가능하였음 보였으며, LSTM 의 입력부분을 변화한 몇가지 딥러닝 모델의 성능을 비교하였다. 이를 통해서 사용자의 보행 상황에 따른 적응적 보행자 항법 파라메터 결정이 가능함의 가능성을 보였다.In this research, the overall construction of the smartphone GPS / INS pedestrian dead reckoning system is detaily described with considering the smartphone sensor measurement properties. Also, the recent android GNSS API which can provide the raw GPS measurement is used. With carrier phase, the cycleslip compensated velocity determination is considered. As a result, the carrier phase /INS integrated pedestrian dead reckoning shows the more precise navigation accuracy than NMEA. Moreover, The deep learning approach is applied in the user context classification to change the parameters in the pedestrian dead reckoning system. The author compares the effect of several transformed inputs for the LSTM model and validate each classification performances.Abstract i Contents ii List of Figures iv List of Tables vii Chapter 1. Introduction 1 1.1 Motivation and Backgrounds 1 1.2 Research Purpose and Contribution 3 1.3 Contents and Methods of Research 3 Chapter 2. Smartphone GPS / INS measurements analysis 4 2.1 Smartphone GNSS measurements 4 2.1.1 Android Raw GNSS Measurements API 4 2.1.2 Raw GPS Measurements Properties 7 2.1.3 Smartphone NMEA Location Provider 8 2.1.4 Pseudorange Based Position Estimation 10 2.1.5 Position Determination Experiment 11 2.2 Smartphone INS Measurements 12 2.2.1 Android Sensor Manager API 12 2.2.2 INS Measurements Properties 13 2.2.3 Noise level, Constant bias, Scale factor, Calibration 14 2.2.4. Accelerometer, Gyroscope Calibration Experiment 17 2.2.5 Magnetometer Ellipse Fitting Calibration 22 2.2.6 Random Bias, Allan Variance Exiperiment 25 2.3 Developed Android Smartphone App 30 Chapter 3. Pedestrian Dead Reckoning 31 3.1 Pedestrian Dead-Reckoning System 31 3.1.1 Attitude Determination Quaternion Kalman Filter 32 3.1.2 Attitude Determination Simulation , Experiment 35 3.1.3 Walking Detection 39 3.1.4 Step Counting, Stride Length 41 3.1.5 Pedestrian Dead Reckoning Experiment 45 Chapter 4. Carrier phase / INS integrated Pedestrian Dead Reckoning 50 4.1 Carrier phase Cycleslip Compensation & Velocity Determination 50 4.1.1 Carrier phase Cycleslip Compensation 50 4.1.2 Android Environment Cycle slip Detection 51 4.1.3 False Alarm & Miss Detection Analysis 55 4.1.4 Doppler, Carrier Based Velocity Estimation 56 4.1.5 Cycle slip Compensation & Velocity Determination Experiment 58 4.2 Raw GPS / INS Integrated Pedestrian Dead Reckoning 63 4.2.1 GPS / INS Integration 63 4.2.2 Position Determination Extended Kalman Filter 65 4.2.3 Raw GPS / INS Integrated Pedestrian Dead Reckoning Experiment 66 Chapter 5. User Context Classification Deep learning for Adaptive PDR 69 5.1 Smartphone Location / Walking Context Classification 69 5.1.1 Smartphone Location / Walking Context Dataset 69 5.1.2 Deep Learning Models 71 5.1.3 Comparison of Input Transformations 72 Chapter 6. Conclusion & Future work 76 Chapter 7. Bibliography 77Maste

    Ambiguity resolution of single frequency GPS measurements

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    This thesis considers the design of an autonomous ride-on lawnmower, with particular attention paid to the problem of single frequency Global Navigation Satellite System (GNSS) ambiguity resolution. An overall design is proposed for the modification of an existing ride-on lawnmower for autonomous operation. Ways of sensing obstacles and the vehicle's position are compared. The system's computer-to-vehicle interface, software architecture, path planning and control algorithms are all described. An overview of satellite navigation systems is presented, and it is shown that existing high precision single frequency GNSS receivers often require time-consuming initialisation periods to perform ambiguity resolution. The impact of prior knowledge of the topography is analysed. A new algorithm is proposed, to deal with the situation where different areas of the map have been mapped at different levels of precision. Stationary and kinematic tests with real-world data demonstrate that when the map is sufficiently precise, substantial improvements in initialisation time are possible. Another algorithm is proposed, using a noise-detecting acceptance test taking data from multiple receivers on the same vehicle (a GNSS com- pass configuration). This allows a more demanding threshold to be used when noise levels are high, and a less demanding threshold to be used at other times. Tests of this algorithm reveal only slight performance improvements. A final algorithm is proposed, using Monte Carlo simulation to account for time-correlated noise during ambiguity resolution. The method allows a fixed failure rate configuration with variable time, meaning no ambiguities are left floating. Substantial improvements in initialisation time are demonstrated. The overall performance of the integrated system is summarised, conclusions are drawn, further work is proposed, and limitations of the techniques and tests performed are identified

    System integration and verification of GNSS baseband processor

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    Satellite navigation, in the last three decades, has seen an evolution bringing up entirely new systems (Galileo) and modernization of existing systems (Global Positioning System). These systems have now changed the environment of the receiver design resulting in the development of Global Navigation Satellite System (GNSS) with new signal processing algorithms. GNSS receiver receives the signals from a GNSS satellite constellation, digitally processes them and provides position, velocity and time. Hardware GNSS receivers have good efficiency, good computational load and low power consumption. Such a hardware GNSS receiver is presented here. GNSS Receiver Reference Design is a fully functional L1 only GNSS receiver design. The main objective for this design is to make fully open access architecture (HW + SW) available to industry partners and researchers for development of GNSS and GNSSenhanced devices, for investigating current GNSS receivers and receiver algorithms and upcoming GNSS receiver standards. Baseband processing generates pre-processed data from received signals. It comprises digital signal processing executed by custom hardware (baseband system) and control processing implemented by a soft-core processor (COFFEE RISC core). The baseband system component performs acquisition and tracking of 6 channels. It currently provides only GPS coarse/acquisition (C/A) code. It is implemented by Field Programmable Gate Array (FPGA) logic, supported by hardware macros. The baseband system and the processor are to be integrated efficiently to manage the receiver activity. The integration is achieved by designing an interface that is compatible with the standard bus architecture. The interface is a shared system bus that contains a register database. The interface is implemented in RTL and verified in functional simulations. In this thesis, another objective of verifying the baseband system is achieved by targeting the maximum code coverage. The results show that this improves the quality of verification and provides good confidence in the design. The coverage numbers prove that the verification is extensive, close to 100%. Finally, synthesis is also needed for verifying the design implementation on gate level. Since the baseband system included many of Xilinx based models, both the subsystems are synthesized on Xilinx Virtex-II Pro platform. The synthesis results provide information on the on-chip area consumption
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