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 non-holonomic 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.
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