Location tracking using multi-sensor fusion and machine learning techniques
With the use of Global Positioning System (GPS), the precise location of any object or person can be determined accurately using satellite signals. However, GPS may not be useful when there are obstacles or building, in particular, in many indoor scenarios. Consequentially, an indoor location track...
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| Format: | Final Year Project |
| Language: | English |
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Nanyang Technological University
2020
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| Online Access: | https://hdl.handle.net/10356/145051 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | With the use of Global Positioning System (GPS), the precise location of any object or person can be determined accurately using satellite signals. However, GPS may not be useful when there are obstacles or building, in particular, in many indoor scenarios.
Consequentially, an indoor location tracking system is necessary for determining position. With reliance on the technologies and sensors that are available, this project aims to develop an indoor positioning system that is independent of the GPS signal.
This report highlights and describes the workings of inertial measurement unit sensors, as well as various machine learning algorithms required to implement an indoor positioning system. |
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