Towards seamless pedestrian navigation
The best methods for processing a positioning solution vary between the positioning technologies. The main methods are examined and the best are chosen and used in the final implementation. The path-loss modelling is the faster method when using BLE. It is slightly more advantageous, although slight...
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
| Published: |
2018
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| Online Access: | https://eprints.nottingham.ac.uk/51886/ |
| _version_ | 1848798596160290816 |
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| author | Peltola, Pekka |
| author_facet | Peltola, Pekka |
| author_sort | Peltola, Pekka |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The best methods for processing a positioning solution vary between the positioning technologies. The main methods are examined and the best are chosen and used in the final implementation. The path-loss modelling is the faster method when using BLE. It is slightly more advantageous, although slightly less accurate, when compared with the very laborious Fingerprinting alternative. For an UWB system, the accurate timing method is the better option over the signal strength measures.
These sensor subsystems produce the positioning solutions that are of different quality. The fusion filter is then the motor, where the information fusion of these subsystems happens. For the fusion, multiple methods exist. Accuracy and computational efficiency are the driving factors in this process of continuous development of an ultimate seamless navigation system.
A truly seamless navigation system uses the best available sensors and methods in the derivation of the most accurate positioning solution. This acquisition relies on the context inference process. The system adapts to all contexts throughout the navigation process. The developed novel seamless positioning system in this thesis was implemented successfully and was proven to operate correctly. The accuracy of the implemented system reaches a level below 4 metres (95%), outdoors. Indoors, the accuracy reaches a level below 2 metres. The availability, the deployment and the existing infrastructure are an issue to be tackled in the future.
The thesis work was conducted as a part of the Marie Curie Initial Training Network project, named Multi-Pos. This project consisted of 15 researchers at different locations in Europe. Part of the thesis is a result of the cooperation between the project partners. Especially the parts of the work done on context detection and the literature review were completed with common effort. |
| first_indexed | 2025-11-14T20:22:17Z |
| format | Thesis (University of Nottingham only) |
| id | nottingham-51886 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:22:17Z |
| publishDate | 2018 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-518862025-02-28T14:07:21Z https://eprints.nottingham.ac.uk/51886/ Towards seamless pedestrian navigation Peltola, Pekka The best methods for processing a positioning solution vary between the positioning technologies. The main methods are examined and the best are chosen and used in the final implementation. The path-loss modelling is the faster method when using BLE. It is slightly more advantageous, although slightly less accurate, when compared with the very laborious Fingerprinting alternative. For an UWB system, the accurate timing method is the better option over the signal strength measures. These sensor subsystems produce the positioning solutions that are of different quality. The fusion filter is then the motor, where the information fusion of these subsystems happens. For the fusion, multiple methods exist. Accuracy and computational efficiency are the driving factors in this process of continuous development of an ultimate seamless navigation system. A truly seamless navigation system uses the best available sensors and methods in the derivation of the most accurate positioning solution. This acquisition relies on the context inference process. The system adapts to all contexts throughout the navigation process. The developed novel seamless positioning system in this thesis was implemented successfully and was proven to operate correctly. The accuracy of the implemented system reaches a level below 4 metres (95%), outdoors. Indoors, the accuracy reaches a level below 2 metres. The availability, the deployment and the existing infrastructure are an issue to be tackled in the future. The thesis work was conducted as a part of the Marie Curie Initial Training Network project, named Multi-Pos. This project consisted of 15 researchers at different locations in Europe. Part of the thesis is a result of the cooperation between the project partners. Especially the parts of the work done on context detection and the literature review were completed with common effort. 2018-07-13 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en arr https://eprints.nottingham.ac.uk/51886/1/thesis-uon-ngi-peltola-4216550.pdf Peltola, Pekka (2018) Towards seamless pedestrian navigation. PhD thesis, University of Nottingham. Seamless pedestrian navigation; Information fusion; GNSS; Inertial IMU ultra-wideband; UWB; Bluetooth; Low energy BLE; Map matching context engine |
| spellingShingle | Seamless pedestrian navigation; Information fusion; GNSS; Inertial IMU ultra-wideband; UWB; Bluetooth; Low energy BLE; Map matching context engine Peltola, Pekka Towards seamless pedestrian navigation |
| title | Towards seamless pedestrian navigation |
| title_full | Towards seamless pedestrian navigation |
| title_fullStr | Towards seamless pedestrian navigation |
| title_full_unstemmed | Towards seamless pedestrian navigation |
| title_short | Towards seamless pedestrian navigation |
| title_sort | towards seamless pedestrian navigation |
| topic | Seamless pedestrian navigation; Information fusion; GNSS; Inertial IMU ultra-wideband; UWB; Bluetooth; Low energy BLE; Map matching context engine |
| url | https://eprints.nottingham.ac.uk/51886/ |