| ONLINE MISALIGNMENT ESTIMATION OF STRAPDOWN NAVIGATION
FOR LAND VEHICLE UNDER DYNAMIC CONDITION |
| Yoonjin Hwang, Yongseop Jeong, In So Kweon, Seibum Choi |
| KAIST |
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| ABSTRACT |
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In recent times, localization and positioning techniques have rapidly developed with the increasing demand for
unmanned vehicles. Most positioning systems for land vehicles based on GPS-IMU, use a non-holonomic constraint to
determine misalignment between sensor and vehicle body frame; however, misalignment estimation depending on nonholonomic
constraint has limitations in high speed environments and there is a lack of observability for roll misalignment.
This paper suggests an online misalignment estimation method under dynamic conditions that violates the non-holonomic
constraint. It provides roll, pitch and yaw misalignment angles of IMU mounted on a vehicle, and corresponding sideslip
angle of the vehicle at the position of IMU. The misalignment estimator is designed as a linear error state Kalman filter, which
takes the results of a strapdown inertial navigation working simultaneously. Computer simulations and real environment
experiments with consumer grade GPS and MEMS IMU are performed to demonstrate the performance and reliability of the
given method. |
| Key Words:
Inertial navigation system, Sensor alignment, Self-calibration |
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Corresponding Author.
Seibum Choi , Email. 
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