A Foot-Mounted Inertial Measurement Unit (IMU) Positioning Algorithm Based on Magnetic Constraint
With the development of related applications, indoor positioning techniques have been more and more widely developed. Based on Wi-Fi, Bluetooth low energy (BLE) and geomagnetism, indoor positioning techniques often rely on the physical location of fingerprint information. The focus and difficulty of...
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doaj-d2b97011b7594428863cd1be4d92e32c2020-11-24T21:10:30ZengMDPI AGSensors1424-82202018-03-0118374110.3390/s18030741s18030741A Foot-Mounted Inertial Measurement Unit (IMU) Positioning Algorithm Based on Magnetic ConstraintYan Wang0Xin Li1Jiaheng Zou2School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, ChinaWith the development of related applications, indoor positioning techniques have been more and more widely developed. Based on Wi-Fi, Bluetooth low energy (BLE) and geomagnetism, indoor positioning techniques often rely on the physical location of fingerprint information. The focus and difficulty of establishing the fingerprint database are in obtaining a relatively accurate physical location with as little given information as possible. This paper presents a foot-mounted inertial measurement unit (IMU) positioning algorithm under the loop closure constraint based on magnetic information. It can provide relatively reliable position information without maps and geomagnetic information and provides a relatively accurate coordinate for the collection of a fingerprint database. In the experiment, the features extracted by the multi-level Fourier transform method proposed in this paper are validated and the validity of loop closure matching is tested with a RANSAC-based method. Moreover, the loop closure detection results show that the cumulative error of the trajectory processed by the graph optimization algorithm is significantly suppressed, presenting a good accuracy. The average error of the trajectory under loop closure constraint is controlled below 2.15 m.http://www.mdpi.com/1424-8220/18/3/741FFTmagnetic fieldgraph optimizationfoot-mounted IMU |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yan Wang Xin Li Jiaheng Zou |
spellingShingle |
Yan Wang Xin Li Jiaheng Zou A Foot-Mounted Inertial Measurement Unit (IMU) Positioning Algorithm Based on Magnetic Constraint Sensors FFT magnetic field graph optimization foot-mounted IMU |
author_facet |
Yan Wang Xin Li Jiaheng Zou |
author_sort |
Yan Wang |
title |
A Foot-Mounted Inertial Measurement Unit (IMU) Positioning Algorithm Based on Magnetic Constraint |
title_short |
A Foot-Mounted Inertial Measurement Unit (IMU) Positioning Algorithm Based on Magnetic Constraint |
title_full |
A Foot-Mounted Inertial Measurement Unit (IMU) Positioning Algorithm Based on Magnetic Constraint |
title_fullStr |
A Foot-Mounted Inertial Measurement Unit (IMU) Positioning Algorithm Based on Magnetic Constraint |
title_full_unstemmed |
A Foot-Mounted Inertial Measurement Unit (IMU) Positioning Algorithm Based on Magnetic Constraint |
title_sort |
foot-mounted inertial measurement unit (imu) positioning algorithm based on magnetic constraint |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2018-03-01 |
description |
With the development of related applications, indoor positioning techniques have been more and more widely developed. Based on Wi-Fi, Bluetooth low energy (BLE) and geomagnetism, indoor positioning techniques often rely on the physical location of fingerprint information. The focus and difficulty of establishing the fingerprint database are in obtaining a relatively accurate physical location with as little given information as possible. This paper presents a foot-mounted inertial measurement unit (IMU) positioning algorithm under the loop closure constraint based on magnetic information. It can provide relatively reliable position information without maps and geomagnetic information and provides a relatively accurate coordinate for the collection of a fingerprint database. In the experiment, the features extracted by the multi-level Fourier transform method proposed in this paper are validated and the validity of loop closure matching is tested with a RANSAC-based method. Moreover, the loop closure detection results show that the cumulative error of the trajectory processed by the graph optimization algorithm is significantly suppressed, presenting a good accuracy. The average error of the trajectory under loop closure constraint is controlled below 2.15 m. |
topic |
FFT magnetic field graph optimization foot-mounted IMU |
url |
http://www.mdpi.com/1424-8220/18/3/741 |
work_keys_str_mv |
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