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Chai, Wennan: Multi-sensor based indoor vehicle and pedestrian navigation. 2019
Inhalt
Acknowledgements
Abstract
Kurzfassung
Contents
List of Figures
List of Tables
List of Abbreviations
List of Symbols
Chapter 1 - Introduction
1.1 Subject of research
1.2 Structure of the dissertation
Chapter 2 - Wi-Fi Based Localization Techniques
2.1 Background and concept of Wi-Fi based localization
2.2 Wi-Fi localization using radio propagation model
2.3 Wi-Fi localization using RSS fingerprinting
2.4 Field experiment and numerical results
2.5 Summary
Chapter 3 - Indoor Vehicle Navigation Using Enhanced INS/Wi-Fi Integration
3.1 System modelling for INS/Wi-Fi integration
3.2 Enhancements using adaptive Kalman filtering and vehicle constraints
3.3 Field experiment and results
3.4 Summary
Chapter 4 - Adapted Indoor Pedestrian Navigation Using PDR/Wi-Fi Integration
4.1 IMU based foot-mounted pedestrian dead reckoning
4.2 Adapted pedestrian dead reckoning with portable devices
4.3 Field experiment and results
4.4 Summary
Chapter 5 - Indoor Attitude Estimation Using INS/Visual-Gyroscope Integration
5.1 Projective geometry and vanishing point detection
5.2 DCM based INS/visual-gyro integration
5.3 Field experiments
5.4 Summary
Chapter 6 - Summary and Conclusions
6.1 Summary
6.2 Conclusions
Appendix A - Artificial Neural Networks
Appendix B - Support vector machine
Appendix C - Unscented Kalman Filtering
Bibliography