학술논문

Dead Reckoning Localization Using a Single Wheel-Mounted IMU With the Simultaneous Estimation of Mounting Parameters
Document Type
Periodical
Author
Source
IEEE Sensors Journal IEEE Sensors J. Sensors Journal, IEEE. 24(3):3797-3810 Feb, 2024
Subject
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Robotics and Control Systems
Wheels
Location awareness
Accelerometers
Angular velocity
Kinematics
Micromechanical devices
Gyroscopes
Dead reckoning
extended Kalman filter (EKF)
ground vehicle localization
mounting parameter estimation
wheel-mounted inertial measurement unit (IMU)
Language
ISSN
1530-437X
1558-1748
2379-9153
Abstract
A single microelectromechanical system (MEMS) inertial measurement unit (IMU) that is mounted on a wheel can achieve a higher vehicle dead reckoning accuracy than a conventional odometer-aided inertial navigation system (INS) because a wheel-mounted IMU can be equivalent to a combination of a virtual odometer and a rotary IMU that can utilize rotation modulation technology. However, the kinematic model used in previous works was simplified without considering the effects of wheel rotation and vehicle body motion on the accelerometers, resulting in very large localization errors, especially when the IMU is not strictly mounted in the center of the wheel and the vehicle speed is higher. Moreover, the mounting parameters, i.e., the misalignment angles and eccentric distance, markedly reduce the localization accuracy. Thus, the parameters should be well estimated and compensated. A kinematic model that considers all major influences, e.g., the wheel rotation, vehicle body motion, and mounting parameters, on the IMU outputs is revealed, and an IMU-wheel alignment and an extended Kalman filter (EKF) are applied to simultaneously estimate the pose of the vehicle and mounting parameters of the IMU with no additional sensors. The results of dozens of experiments show that the proposed method achieves higher accuracy with regards to the position, heading, and velocity than the state-of-the-art method and that the localization accuracy is increased by approximately 1/3.