Wireless position sensing and normalization of embedded resonant sensors using a resonator array

Abstract

In this work, four square, planar resonators with unique frequency windows were used to form a 2 by 2 array for wireless position determination and normalization of position-dependent, embedded resonant sensors. First, a master table of S|21| gain and phase data was collected at 8100 positions. Automated scripts extracted the characteristic gain and phase peaks and used cubic interpolation to expand the master table to 7,157,160 unique angle and coordinate positions. An unknown position is then determined by comparing its S|21| measurements to this table. To further improve the position accuracy, multiple measurements are collected on linear flyby trajectories. The average and standard deviation of predicted position offset from true value using this method were 3.2 and 2.3 mm, respectively. To test normalization of a position dependent sensor, a spiral resonant sensor was placed underneath the square array. The sensor signal was modulated using varying amounts of water on the sensor surface. A corrected reading was determined using four different flyby trajectories using the position array data to adjust the signal based on position. We found that average errors of the normalized signals were between 0.04 to 0.15 MHz at lower water volume (0.5 mL) and -0.53 to -0.74 MHz at higher water volume (2.0 mL). In its current state, the positional array can be used for asset tracking or feedback control and the sensor normalization can be used to improve the measurement accuracy of embedded sensors. This technique can be further improved by collecting more accurate master calibration data using an automated system.