Motion Estimation for a Compact Electrostatic Microscanner via Shared Driving and Sensing Electrodes in Endomicroscopy.

We present a method to estimate high frequency rotary motion of a highly compact electrostatic micro-scanner using the same electrodes for both actuation and sensing. The accuracy of estimated rotary motion is critical for reducing blur and distortion in image reconstruction applications with the micro-scanner given its changing dynamics due to perturbations such as temperature. To overcome the limitation that no dedicated sensing electrodes are available in the proposed applications due to size constraints, the method adopts electromechanical amplitude modulation (EAM) to separate motion signal from parasitic capacitance feedthrough, and a novel non-linear measurement model is derived to characterize the relationship between large out-of-plane angular motion and circuit output. To estimate motion, an extended Kalman filter (EKF) and an unscented Kalman filter (UKF) are implemented, incorporating a process model based on the micro-scanner's parametric resonant dynamics and the measurement model. Experimental results show that compared to estimation without using the measurement model, our method is able to improve the rotary motion estimation accuracy of the micro-scanner significantly, with a reduction of root-mean-square error (RMSE) in phase shift of 86.1%, and a reduction of RMSE in angular position error of 78.5 %.