Position Estimation and Smooth Tracking with a Fuzzy Logic-Based Adaptive Strong Tracking Kalman Filter for Capacitive Touch Panels

This work presents a novel 7-inch capacitive touch panel (CTP) system with a smooth tracking algorithm that accurately estimates the position where the panel is touched and tracks the trajectory of touch. The proposed CTP system consists of a micro-controller unit, sensor IC, and interface board. When a user draws at different speeds, the measurement noise caused by the sensor IC induces an error in the touched position and zigzag trajectory, especially when the motion is slow. The fuzzy logic-based adaptive strong tracking Kalman filter (FLASTKF) method is implemented in a CTP system to mitigate the effect of measurement noise and provide a smooth tracking trajectory at different speeds. Moreover, the approach effectively measures and quantifies the "smoothness" of the touched trajectory. Experimental results indicate that the proposed method reduces the measurement noise and decreases the mean tracking error by 85.4% over that achieved using the moving average filter (MAF).