The Setting of IMU Parameters in Kalman Filtering-based Information Fusion
arXiv:2608.21433v1 Announce Type: new Abstract: The setting or tuning of specifications for the inertial measurement unit (IMU) is tricky in sensor fusion. The underneath conundrum is caused by the fact that the working condition of IMU is more complex than the stationary calibration scenario. Since the noises and biases instabilities calibrated under static condition cannot accommodate other cases, the effective tuning of IMU parameters largely hinges on the experience or profound understandin
Overview
arXiv:2608.21433v1 Announce Type: new Abstract: The setting or tuning of specifications for the inertial measurement unit (IMU) is tricky in sensor fusion. The underneath conundrum is caused by the fact that the working condition of IMU is more complex than the stationary calibration scenario. Since the noises and biases instabilities calibrated under static condition cannot accommodate other cases, the effective tuning of IMU parameters largely hinges on the experience or profound understanding of the system. In the current work, the setting method of IMU parameters based on Allan variance calibration is delved into within the Kalman filtering framework. Specifically, the relationship between the power sepctral density and Allan variance is leveraged in formulating the process uncertainty in continuous-time filtering. Two typical IMU-based sensor fusion systems are considered to show the feasibility and effectiveness of this parameter setting process.
Source
Originally published at arxiv.org.
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Source: https://arxiv.org/abs/2608.21433