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GNSS for Train Localisation Performance Evaluation and Verification

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GNSS for Train Localisation Performance Evaluation and Verification GNSS for Train Localisation Performance Evaluation and Verification Von der Fakult¨at fur¨ Maschinenbau der Technischen Universit¨at Carolo-Wilhelmina zu Braunschweig zur Erlangung der Wurde¨ eines Doktor-Ingenieurs (Dr.-Ing.) genehmigte Dissertation von: Debiao Lu M.Sc. aus: Nantong, Jiangsu, China eingereicht am: 20.02.2014 mundliche¨ Prufung¨ am: 17.06.2014 Gutachter: Prof. Dr.-Ing. Dr. h. c. mult. Eckehard Schnieder Prof. Dr.-Ing. Jurgen¨ Beyer 2014 \Measure what can be measured, and make measurable what cannot be measured." Galileo Galilei Acknowledgements This dissertation is based on my research work in Institute for Traffic Safety and Automation Engineering (iVA) at TU Braunschweig in the last four years. Without the sincere support from many people, it would not have been written. I would like to express my gratitude to all the people who made this dissertation possible. Because of you, my research experience in Germany has become a story that I will always remember. First, I owe my far deepest gratitude to my supervisor Prof. Dr.-Ing. Dr. h.c. mult. Eckehard Schnieder, who guided me into the rigorous and precise research world. He gave me not only the freedom to explore on my own, but also the structuralised methods to describe every concept clearly. This will be helpful for my whole life. I would like to thank Prof. Dr.-Ing. J¨urgenBeyer for the acceptance of co- supervising my dissertation. His intensive knowledge in GNSS helped me to es- tablish a more stable ground for this dissertation. The constructive discussions and valuable comments are very useful for my further research. I also would like to thank Prof. Dr.-Ing. Karsten Lemmer for hosting my doctor defence. He gave me useful suggestions for the defence in a preliminary talk. All the colleagues at iVA are acknowledged for their contribution to an enjoyable working environment. I would like to extend a special gratitude to Federico Grasso Toro and Dirk Spiegel for giving corrections for this dissertation. Furthermore I am very grateful to the Chinese Scholarship Council (CSC) to provide the scholarship for my research. This scholarship also gives me possibilities to extend the friendship with some Chinese friends from Beijing Jiaotong University. Finally I would like to express my gratitude to my family. This dissertation is ded- icated to my parents, Daoshan Lu and Yamin Wang, who decided 27 years ago to give birth to me as the second child in the family and supported me to go so far. Braunschweig, 30.06.2014 Debiao Lu v Abstract Global Navigation Satellite Systems (GNSS) are potentially applicable for various railway applications, especially the safety-related applications such as train local- isation for the purpose of train control. In order to integrate GNSS for train local- isation, a trustable stand-alone GNSS-based localisation unit should be developed. Then to comply with EN 50126 (reliability, availability, maintainability, and safety; RAMS) standards, the demonstration of GNSS quality of service (QoS) should be evaluated in consistent with RAMS. However there are currently no appropriate performance evaluation methods on GNSS for railway safety-related applications. This dissertation identifies the required performance for train localisation in con- sideration of GNSS QoS and railway RAMS. The common and different properties of the performance are analysed in detail using consistent attribute hierarchy struc- tures based on UML class diagram. Then formalised performance requirements are proposed quantitatively on four properties (accuracy, reliability, availability, and safety integrity). After that, the evaluation and verification methodologies are in- troduced. The evaluation methodology is using a reference measurement system for GNSS receiver measured train location accuracy identification, and a stochastic Petri net (SPN) model for GNSS receiver measured train location accuracy categor- isation. The SPN model illustrates the GNSS receiver measured train locations into three states (up state, degraded state, and faulty state). Then the four proposed properties are allocated and estimated formally using the three states in the SPN model. The verification methodology is used to verify the GNSS receiver meas- ured train location in real time based on a localisation unit. The GNSS receiver measured train locations are verified using hypothesis testing methods based on the accurate digital track map provided beforehand. Then train location estimation from the localisation unit is verified according to the mileage of the train. With the verified train location estimation from the localisation unit, the corresponding safety margin for each train location is calculated. The data for evaluation and verification methodologies are collected from a test train running on a railway track in High Tatra Mountains. The results show an approach of the possible certification procedure for the GNSS receivers in railway safety-related applications. vii Kurzfassung Globales Satellitennavigationssystem (GNSS) k¨onnenf¨urverschiedene Anwendun- gen im Schienenverkehr, vor allem f¨ursicherheitsrelevante Anwendungen wie Zugor- tung zum Zweck der Zugsicherung gest¨utztwerden. Um GNSS f¨urZugortung zu integrieren, muss eine eigenst¨andigesatellitenbasierte Ortungseinheit entwick- elt werden. Um die Entwicklung in Einklang mit EN 50126 (Uberlebensf¨ahigkeit,¨ Verf¨ugbarkeit, Instandhaltbarkeit, und Sicherheit; RAMS) durchzuf¨uhren,muss der Nachweis der G¨utevon GNSS (Quality of Service; QoS) entsprechend in Einklang mit dieser Norm bewertet werden. Allerdings gibt es zurzeit keine RAMS Bewer- tungsverfahren f¨ursatellitenbasierte sicherheitsrelevante Anwendungen im Schien- enverkehr. Diese Dissertation identifiziert die notwendigen Anforderungen f¨urdie Zugortung unter Ber¨ucksichtigung der G¨utevon GNSS und den bestehenden Normen bez¨uglich RAMS im Schienenverkehr. Die gemeinsamen und unterschiedlichen Eigenschaften der Anforderungen werden detailliert mit Nutzung einer Attributhierarchie basier- end auf UML-Klassendiagrammen dargestellt. Danach werden formalisierte Leis- tungsanforderungen quantitativ f¨urvier Eigenschaften (Genauigkeit, Zuverl¨assigkeit, Verf¨ugbarkeit und Sicherheitsintegrit¨at)vorgeschlagen. Darauf aufbauend werden die Bewertungs- und Verifikations- Methoden eingef¨uhrt. Die Bewertungsmeth- ode nutzt ein Referenzmesssystem zur Identifikation der Zugortungsgenauigkeit der GNSS Empf¨angerund ein stochastischen Petri-Netz-Modell (SPN-Modell) f¨urdie Kategorisierung der GNSS Empf¨angerZugortmessungen. Das SPN-Modell ver- anschaulicht die GNSS Empf¨angerZugortmessungen in drei Zust¨anden(up state, degraded state, faulty state). Dann werden die vier vorgeschlagenen Eigenschaften zugeordnet und formal mit Nutzung der drei Zust¨andeim SPN-Modell gesch¨atzt. Die Verifikationsmethode wird verwendet, um die GNSS Empf¨anger Zugortmessun- gen in Echtzeit zu verifizieren. Die GNSS Empf¨anger Zugortmessungen werden mit einer Hypothesentestmethode auf der Grundlage der genauen digitalen Streckenk- arte verifiziert. Mit der verifizierten gesch¨atztenZugortmessung wird der resultier- ende Sicherheitsbereich f¨urjeden Zugort berechnet. Die Daten f¨urdie Auswertungs- und Verifikationsmethoden wurden von einem Zug im Regelbetrieb auf einer Eisenbahnstrecke in der Hohen Tatra gesammelt. Die Ergebnisse dieser Arbeit zeigen einen Ansatz der m¨oglichen Zertifizierungsverfahren f¨urdie GNSS-Empf¨angerf¨ursicherheitsrelevante Anwendungen im Schienenverkehr. ix Contents Acknowledgements v Abstract vii Kurzfassung ix Contents xi List of Figures xv List of Tables xix 1 Introduction 1 1.1 Purpose of the Dissertation . .3 1.2 Structure of the Dissertation . .6 2 State of the Art 11 2.1 Train Detection and Localisation Methods in Railway . 11 2.2 GNSS for Train Localisation Researches and Applications . 12 2.2.1 GNSS for Train Localisation Research Projects . 14 2.2.2 GNSS for Train Localisation Researches at iVA . 14 2.2.3 GNSS for Train Localisation Applications . 14 2.3 Migration of GNSS QoS and Railway RAMS . 17 2.4 Evaluation of GNSS Receiver for Train Localisation Performance . 19 2.5 Verification of GNSS-based Localisation Unit Performance . 20 3 Fundamentals of Used Means of Descriptions and Theories 23 3.1 UML Class Diagram . 23 3.1.1 Class . 24 3.1.2 Relationships . 24 3.1.3 Diagrams . 27 3.2 Consistent Terminology . 27 3.2.1 Attribute Hierarchy for Concept Intension . 28 3.2.2 System as a Concept in UML Class Diagram and Attribute Hierarchy . 30 3.2.3 Relation between Terms . 32 3.3 Formalisation with Petri nets . 34 xi Contents xii 3.3.1 Place/Transition nets . 34 3.3.2 Stochastic Petri nets . 36 3.4 Probability and Distribution . 38 3.4.1 Probability . 38 3.4.2 Distributions . 40 3.4.3 Distribution Fitting . 42 3.5 Optimal Detection Theory . 43 3.5.1 Hypothesis Testing . 43 3.5.2 Hypothesis Testing for One Sample . 44 3.5.3 Hypothesis Testing for Two Samples . 45 3.5.4 Quantitative Attribute for Detection Results . 46 4 GNSS Measurement Principles and Performance Requirements 51 4.1 Localisation Terminology . 51 4.2 Three GNSS-related Systems . 53 4.2.1 GNSS Structure . 55 4.2.2 Digital Track Map . 56 4.2.3 Reference Measurement System Structure . 58 4.2.4 GNSS-based Localisation Unit Structure and Functions . 59 4.3 GNSS Localisation Principles . 60 4.3.1 Concept of Ranging Using Time of Arrival Measurements . 60 4.3.2 Measurement Errors and Satellite Geometry . 64 4.3.3 Environmental Scenarios in GNSS for Train Localisation . 67 4.4 GNSS Performance Requirements from Service Provider
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