Abstract
Wearable devices often process sensor data in separate modules, which can cause redundant computation and increase power consumption. Additionally, traditional factory calibrations may suffer from thermal hysteresis as temperatures fluctuate. To address these limitations, a centralized sensor fusion architecture is disclosed that can utilize a tightly coupled Extended Kalman Filter. This centralized system is configured to collectively process inputs from multiple inertial measurement units, a magnetometer, and corresponding temperature sensors. The architecture can perform online bias estimation based on temperature profiles and route bias corrections to other modules. This unified model may provide three-degree-of-freedom or sixdegree- of-freedom orientation estimation, continuous sensor calibration, and frame deformation tracking. Centralizing these operations can reduce computational redundancy and optimize power management.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Jia, Zhiheng; Paul, Mrinal Kanti; Duenner, Andrew Christoper; and Zhang, Qiyue, "Centralized Multi-Sensor Calibration and Fusion for Extended Reality Glasses", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/12229