Indoor location tracking using IMU and UWB
This report investigates the accuracy of an indoor tracking system utilizing a sensor fusion algorithm, which integrates two single navigation devices: IMU (Inertial Measurement Unit) and UWB (Ultra-wideband) technologies. These positioning methods are tested with various sensor configurations, and...
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2024
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sg-ntu-dr.10356-1762062024-05-17T15:43:43Z Indoor location tracking using IMU and UWB Gouw, Hugo Sebastian Law Choi Look School of Electrical and Electronic Engineering ECLLAW@ntu.edu.sg Engineering This report investigates the accuracy of an indoor tracking system utilizing a sensor fusion algorithm, which integrates two single navigation devices: IMU (Inertial Measurement Unit) and UWB (Ultra-wideband) technologies. These positioning methods are tested with various sensor configurations, and their performance is compared against ground truth data to evaluate both accuracy and energy efficiency. The sensor fusion algorithm operates by designating one sensor as the primary source and refining its measurements using data from the other sensor. The study illustrates how the sensor fusion algorithm successfully addresses the limitations of both IMU and UWB devices. While IMU performs well in maintaining accuracy along a straight-line trajectory, it suffers from the accumulation of heading errors. On the other hand, UWB exhibits greater reliability in managing heading changes but struggles with inconsistent data in a straight-line trajectory. Bachelor's degree 2024-05-15T01:21:54Z 2024-05-15T01:21:54Z 2024 Final Year Project (FYP) Gouw, H. S. (2024). Indoor location tracking using IMU and UWB. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/176206 https://hdl.handle.net/10356/176206 en A3086-231 application/pdf Nanyang Technological University |
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This report investigates the accuracy of an indoor tracking system utilizing a sensor fusion algorithm, which integrates two single navigation devices: IMU (Inertial Measurement Unit) and UWB (Ultra-wideband) technologies. These positioning methods are tested with various sensor configurations, and their performance is compared against ground truth data to evaluate both accuracy and energy efficiency. The sensor fusion algorithm operates by designating one sensor as the primary source and refining its measurements using data from the other sensor. The study illustrates how the sensor fusion algorithm successfully addresses the limitations of both IMU and UWB devices. While IMU performs well in maintaining accuracy along a straight-line trajectory, it suffers from the accumulation of heading errors. On the other hand, UWB exhibits greater reliability in managing heading changes but struggles with inconsistent data in a straight-line trajectory. |
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Law Choi Look |
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Law Choi Look Gouw, Hugo Sebastian |
format |
Final Year Project |
author |
Gouw, Hugo Sebastian |
author_sort |
Gouw, Hugo Sebastian |
title |
Indoor location tracking using IMU and UWB |
title_short |
Indoor location tracking using IMU and UWB |
title_full |
Indoor location tracking using IMU and UWB |
title_fullStr |
Indoor location tracking using IMU and UWB |
title_full_unstemmed |
Indoor location tracking using IMU and UWB |
title_sort |
indoor location tracking using imu and uwb |
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Nanyang Technological University |
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2024 |
url |
https://hdl.handle.net/10356/176206 |
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1806059862136717312 |