Stochastic Modelling to Enable Ultrafast High Resolution Capacitive Position Sensing of a Resonant MEMS Mirror

摘要

With the increased interest in adoption of rapid prototyping processes for high throughput manufacturing lines, uncertainties in topology and physics arise. These uncertainties cannot be captured anymore by conventional simulation techniques without major efforts. Thus grows the necessity to compensate adverse effects on the side of signal processing rather than in the sensor front end. This can be done utilizing models which incorporate available prior knowledge. It is shown that utilizing a model for the motion of a resonant MEMS mirror, the uncertainty of the position estimate can be reduced to a level which would otherwise be prohibited by thermal noise. To meet the requirements with respect to update rate and latency, it is mandatory that the algorithm can be implemented in hardware. This is done in an FPGA platform with a specifically designed analogue front-end.