Next Article in Journal
Early Detection of Exposure to Toxic Chemicals Using Continuously Recorded Multi-Sensor Physiology
Previous Article in Journal
Wideband Circular Polarized Dielectric Resonator Antenna Array for Millimeter-Wave Applications
Article

Applying a ToF/IMU-Based Multi-Sensor Fusion Architecture in Pedestrian Indoor Navigation Methods

Laboratory of Space Technologies, Embedded Systems, Navigation and Avionic (LASSENA), Department of Electrical Engineering, École de Technologie Supérieure, Montreal, QC H3C 1K3, Canada
*
Author to whom correspondence should be addressed.
Academic Editors: Michael J. Korenberg and Umar Iqbal
Sensors 2021, 21(11), 3615; https://doi.org/10.3390/s21113615
Received: 24 April 2021 / Revised: 18 May 2021 / Accepted: 20 May 2021 / Published: 22 May 2021
The advancement of indoor Inertial Navigation Systems (INS) based on the low-cost Inertial Measurement Units (IMU) has been long reviewed in the field of pedestrian localization. There are various sources of error in these systems which lead to unstable and unreliable positioning results, especially in long term performances. These inaccuracies are usually caused by imperfect system modeling, inappropriate sensor fusion models, heading drift, biases of IMUs, and calibration methods. This article addresses the issues surrounding unreliability of the low-cost Micro-Electro-Mechanical System (MEMS)-based pedestrian INS. We designed a novel multi-sensor fusion method based on a Time of Flight (ToF) distance sensor and dual chest- and foot-mounted IMUs, aided by an online calibration technique. An Extended Kalman Filter (EKF) is accounted for estimating the attitude, position, and velocity errors, as well as estimation of IMU biases. A fusion architecture is derived to provide a consistent velocity measurement by operative contribution of ToF distance sensor and foot mounted IMU. In this method, the measurements of the ToF distance sensor are used for the time-steps in which the Zero Velocity Update (ZUPT) measurements are not active. In parallel, the chest mounted IMU is accounted for attitude estimation of the pedestrian’s chest. As well, by designing a novel corridor detection filter, the heading drift is restricted in each straightway. Compared to the common INS method, developed system proves promising and resilient results in two-dimensional corridor spaces for durations of up to 11 min. Finally, the results of our experiments showed the position RMS error of less than 3 m and final-point error of less than 5 m. View Full-Text
Keywords: indoor navigation; time of flight sensor; foot-mounted INS; online calibration; pedestrian navigation; IMU inertial navigation indoor navigation; time of flight sensor; foot-mounted INS; online calibration; pedestrian navigation; IMU inertial navigation
Show Figures

Figure 1

MDPI and ACS Style

Farhangian, F.; Sefidgar, M.; Landry, R.J. Applying a ToF/IMU-Based Multi-Sensor Fusion Architecture in Pedestrian Indoor Navigation Methods. Sensors 2021, 21, 3615. https://doi.org/10.3390/s21113615

AMA Style

Farhangian F, Sefidgar M, Landry RJ. Applying a ToF/IMU-Based Multi-Sensor Fusion Architecture in Pedestrian Indoor Navigation Methods. Sensors. 2021; 21(11):3615. https://doi.org/10.3390/s21113615

Chicago/Turabian Style

Farhangian, Farzan, Mohammad Sefidgar, and Rene J. Landry 2021. "Applying a ToF/IMU-Based Multi-Sensor Fusion Architecture in Pedestrian Indoor Navigation Methods" Sensors 21, no. 11: 3615. https://doi.org/10.3390/s21113615

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop