MEMS Gyroscope Demodulation with Asynchronous ADC Sampling
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Solution Overview
Problem
Existing MEMS gyroscope demodulation methods face challenges in accurately separating real and quadrature components due to manufacturing imperfections, leading to significant quadrature bias and noise interference, which requires high dynamic range and precise phase accuracy, and are hindered by the difficulty in maintaining synchronous sampling at fast clock rates.
Innovation Solution
Employing an asynchronous analogue-to-digital converter (ADC) operating at a sampling rate of at least 50 times the resonant frequency, combined with a synchronous clock for sector-based demodulation, allowing for higher sampling rates without synchronous constraints, and using correlation functions to selectively combine samples based on the resonator's cycle sectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If synchronous sampling is used at fast clock rates, then phase accuracy is improved, but maintaining synchronous sampling becomes difficult
Solution Approach 1:
The patent replaces the mechanical/synchronous sampling system with an asynchronous sampling system. Instead of requiring the ADC to sample exactly at specific phases of the resonator cycle, the system continuously samples asynchronously and then uses digital signal processing to extract the in-phase and quadrature components. This substitution eliminates the difficulty of maintaining synchronous sampling while preserving measurement accuracy through post-processing.
2Measurement precision
If sampling rate is increased to reduce noise, then signal-to-noise ratio is improved, but synchronous constraints become more difficult to maintain
Solution Approach 1:
The patent introduces dynamic asynchronous sampling where the sampling rate can be increased to reduce noise, but the timing constraints are relaxed. The system dynamically adjusts by continuously sampling at high rates and then using correlation functions to extract the desired signal components. This allows the system to benefit from higher sampling rates for noise reduction without being constrained by strict synchronous timing requirements.
3Measurement precision
If quadrature bias is reduced through better manufacturing, then measurement precision is improved, but manufacturing complexity increases
Solution Approach 1:
The patent extracts and separates the quadrature component from the in-phase component through asynchronous sampling and digital signal processing. By using correlation functions with sine and cosine references, the system can isolate and measure the quadrature bias independently, then compensate for it in software. This removes the need for perfect manufacturing alignment, as the quadrature error is measured and corrected digitally rather than requiring precise mechanical alignment.
4Measurement precision
If dynamic range is increased to handle quadrature bias, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces the need for high dynamic range hardware with digital signal processing. Instead of requiring the ADC and front-end circuitry to handle very large dynamic ranges to accommodate quadrature bias, the system uses asynchronous sampling with correlation functions to extract components digitally. This substitution moves the dynamic range requirement from the hardware domain to the software processing domain, reducing hardware complexity while maintaining measurement precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly improves the signal-to-noise ratio by averaging out noise through increased sampling, achieving accurate demodulation of real and quadrature components with minimal hardware updates, enhancing the precision and efficiency of MEMS gyroscope signal processing.
Implementation Method 1
piezoelectric versions exist (i.e. where the forces applied to the ring and the signals detected from the ring are created / detected using inductive, capacitive or piezoelectric electrodes)
Implementation Method 2
An annular mechanical resonator 1 is vibrated at its resonant frequency (typically 14 kHz) by the primary drive electrode P D
Implementation Method 3
When the annular resonator is rotated about an axis normal to its plane, the Coriolis effect causes a secondary vibration in an orthogonal direction that pulls energy into the secondary mode
Data Source
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AI summary
A method of demodulating a MEMS sensor pickoff signal from a vibrating resonator of said sensor, the method comprising: sampling the pickoff signal with an asynchronous ADC at a sampling rate of at least 50 times the resonant frequency of the resonator to generate a stream of samples; generating a first value by combining samples from said stream of samples according to a selected operation, said operation being selected in dependence on a synchronous clock signal that is synchronous to the resonant frequency of the resonator, said synchronous clock signal having a frequency at least twice the resonant frequency of the resonator; and counting the number of samples contributing to the first value. The increased sampling rate of the pickoff signal allows a much higher number of samples to be taken into account, thereby reducing noise. However, the ADC is not driven by a synchronous clock, but instead operates asynchronously from the resonator of the MEMS sensor. A lower frequency synchronous clock is used to keep track of which samples fell within particular sectors of the resonator cycle. This information can then be used to select an appropriate way to combine the samples.