High Resolution Frequency Measurement Techniques for Relaxation Oscillator Based Capacitive Sensors

This work presents high resolution and adaptable frequency measurement techniques for relaxation oscillator based capacitive sensors. The techniques rely on extremely simple hardware such as a 1-bit coarse voltage quantizer to generate a 1-bit data stream and subsequently determine frequencies with resolutions greater than 20 bits from the 1-bit data stream. The proposed readouts are based on two types of 1-bit hardware approaches with Nyquist sampling in one approach and oversampling in the other. The first approach employs a Nyquist rate sampled 1-bit comparator while the second approach relies on an oversampled 1-bit quantizer based delta-sigma modulator (DSM) as a hardware to generate the bit stream. High resolution frequency is estimated from the 1-bit data stream using parametric, non-parametric and compressed sensing approaches. We provide detailed study and measurement results comparing the performance of the proposed techniques for test inputs with different frequencies and amplitudes and multiple signal shapes including sine, square, triangular and sawtooth. We show that the 1-bit comparator along with the CS approach provides the best performance across all input amplitude, frequency and shapes. A capacitive water level sensor was implemented in a PCB and embedded in a conventional square wave relaxation oscillator to verify the proposed technique. Measurement results show that incremental SNRs can be achieved only by increasing the 1-bit data stream length without any change in the hardware thereby demonstrating the adaptability of the technique based on an application requirement.

Automated summary

This work introduces high resolution and adaptable frequency measurement techniques for capacitive sensors, utilizing simple hardware and different 1-bit hardware approaches to determine frequencies with resolutions greater than 20 bits from a 1-bit data stream, and estimating high resolution frequency using parametric, non-parametric and compressed sensing methods. Experimental results demonstrate that the 1-bit comparator along with the CS approach provides the best performance across different input conditions.