Problem
Research questions and friction points this paper is trying to address.
IMU parameters
Kalman filtering
sensor fusion
Allan variance
The Setting of IMU Parameters in Kalman Filtering-based Information Fusion
🤖 AI Summary
研究通过Allan方差校准法在卡尔曼滤波框架下设置IMU参数，解决了复杂工作条件下IMU参数难以有效调整的问题。
📝 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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Allan Variance Calibration
Kalman Filtering
IMU Parameters Setting
Power Spectral Density
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