Capacitive sensor signal processing based on decentralized Kalman filtering

The determination of the angular position and angular velocity is a frequent task in the field of sensing applications. Despite the presence of harsh environmental conditions both accuracy and robustness are desired. Because of their insensitivity to such environmental influences, non-contacting capacitive sensors are able to meet these industrial requirements. This paper proposes an approach for the robust and accurate estimation of angular position and speed for capacitive sensors based on decentralized Kalman filtering. The computational complexity can be reduced considerably while maintaining high accuracy. Furthermore decentralized filtering allows additional options for fault detection. Faults like segment drift and segment breakdown which, are common in practical implementations, are analyzed in detail.