Implementation of Passive Telemetry RF Sensor System Using Unscented Kalman Filter Algorithm

Abstract

This article describes a newly designed and implemented capacitive sensor system. An Unscented Kalman Filter (UKF) algorithm based passive telemetry RF sensor system was modeled with parasitic parameters over a range of high frequencies of approximately 200 KHz. And the system was also successfully implemented on the DSP. Under the constraints that it should be “wireless,” “implantable,” and “batteryless,” the system was simply built to consisted of passive components R, L and C by the inductive coupling principle, and it focused on the accurate estimation of a capacitive parameter in the secondary part. The UKF algorithm, which can coped with the drawbacks of the extended Kalman filter in noisy nonlinear systems, was applied to estimate the capacitive parameter with nonlinearity. The input/output learning data for the UKF algorithm were acquired from the specially designed phase difference detector and amplitude detector. The newly suggested parameter estimation technique can be easily applied to the precise measurement system, which should coped with sensitive environmental changes, such as changes in pressure or humidity.