Estimators for Inductive-Coupling Based Batteryless Wireless High-Frequency Sensing

This paper develops estimation algorithms for inductively coupled batteryless wireless sensors. In such sensors, the objective is to estimate the capacitance of the embedded sensor by the measuring the influence of the sensor on an inductively coupled interrogator. The primary challenge in capacitance-estimation is the need for an accurate knowledge of the mutual inductance between the sensor and interrogator, which, varies with the location and alignment of the interrogator. Existing estimation methods that overcome this challenge are too slow for high-frequency sensing applications like microphones. This paper develops solutions designed to address the above limitation. A nonlinear adaptive observer and a cascaded filter are developed and evaluated for high-frequency capacitance estimation. Results show that the cascaded filter can accurately estimate high frequency capacitance changes with varying mutual inductance.