Sensor fusion for smartphone pose estimation
With the increasing sophistication of smartphone applications, accurate positioning and tracking have become a vital component of various cutting-edge technologies where sensor fusion is essential in the integration of data from multiple sensors to achieve a more accurate and reliable estimation of...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/166838 |
| _version_ | 1826117474317238272 |
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| author | Ho, Kok Pin |
| author2 | Arokiaswami Alphones |
| author_facet | Arokiaswami Alphones Ho, Kok Pin |
| author_sort | Ho, Kok Pin |
| collection | NTU |
| description | With the increasing sophistication of smartphone applications, accurate positioning and tracking have become a vital component of various cutting-edge technologies where sensor fusion is essential in the integration of data from multiple sensors to achieve a more accurate and reliable estimation of the state of a system. This project proposes an innovative approach to improve the performance of Kalman filter algorithms, specifically, the Enhanced Error-State Kalman Filter (ESKF), for smartphone pose estimation. The ESKF method is a more efficient and robust alternative to the commonly used Extended Kalman Filter (EKF) method, particularly for nonlinear systems. ESKF requires prior construction of an error process that relates the error variables associated with the pose estimation system model. Besides, a magnetometer correction model is introduced which enables better magnetic tolerance and compensation than the conventional IMU filter. The results demonstrate that the enhanced ESKF method achieves remarkable precision in estimating three-dimensional rotations with error typically below 5° under a non-disturbed environment. |
| first_indexed | 2024-10-01T04:27:51Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/166838 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:27:51Z |
| publishDate | 2023 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1668382023-07-07T15:54:05Z Sensor fusion for smartphone pose estimation Ho, Kok Pin Arokiaswami Alphones School of Electrical and Electronic Engineering EAlphones@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering With the increasing sophistication of smartphone applications, accurate positioning and tracking have become a vital component of various cutting-edge technologies where sensor fusion is essential in the integration of data from multiple sensors to achieve a more accurate and reliable estimation of the state of a system. This project proposes an innovative approach to improve the performance of Kalman filter algorithms, specifically, the Enhanced Error-State Kalman Filter (ESKF), for smartphone pose estimation. The ESKF method is a more efficient and robust alternative to the commonly used Extended Kalman Filter (EKF) method, particularly for nonlinear systems. ESKF requires prior construction of an error process that relates the error variables associated with the pose estimation system model. Besides, a magnetometer correction model is introduced which enables better magnetic tolerance and compensation than the conventional IMU filter. The results demonstrate that the enhanced ESKF method achieves remarkable precision in estimating three-dimensional rotations with error typically below 5° under a non-disturbed environment. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-05-10T01:43:53Z 2023-05-10T01:43:53Z 2023 Final Year Project (FYP) Ho, K. P. (2023). Sensor fusion for smartphone pose estimation. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166838 https://hdl.handle.net/10356/166838 en A3048-221 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering Ho, Kok Pin Sensor fusion for smartphone pose estimation |
| title | Sensor fusion for smartphone pose estimation |
| title_full | Sensor fusion for smartphone pose estimation |
| title_fullStr | Sensor fusion for smartphone pose estimation |
| title_full_unstemmed | Sensor fusion for smartphone pose estimation |
| title_short | Sensor fusion for smartphone pose estimation |
| title_sort | sensor fusion for smartphone pose estimation |
| topic | Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering |
| url | https://hdl.handle.net/10356/166838 |
| work_keys_str_mv | AT hokokpin sensorfusionforsmartphoneposeestimation |