MEMS Sensor Equalization Using NVM-Stored Measured Parameters
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Solution Overview
Problem
MEMS sensors, such as accelerometers and gyroscopes, exhibit manufacturing and processing variations that lead to undesirable peaking and resonance characteristics in their output signals, which current technologies fail to adequately address.
Innovation Solution
Storing measured sensor parameters, including resonant frequency, quality factor, and gain, in a non-volatile memory of a sensor signal processor, allowing a digital signal processor to equalize sensor data using these parameters to compensate for manufacturing variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manufacturing variations are present in MEMS sensors, then production cost and throughput are improved, but signal accuracy and consistency deteriorate due to peaking and resonance characteristics
Solution Approach 1:
The patent measures and stores individual sensor parameters (resonant frequency, quality factor, gain) during manufacturing testing, then uses these pre-characterized parameters to compute equalization filter coefficients before the sensor is deployed. This preliminary characterization allows the sensor to maintain high signal accuracy despite manufacturing variations, while still enabling mass production.
Solution Approach 2:
The patent changes the parameters of the signal processing system by computing custom equalization filter coefficients based on measured sensor characteristics. These coefficients are stored in non-volatile memory and applied during operation to compensate for manufacturing variations, thereby maintaining signal accuracy without sacrificing production efficiency.
2Measurement precision
If individual part measurements are performed for each MEMS sensor, then signal accuracy is improved, but measurement time and device complexity increase
Solution Approach 1:
The patent performs individual sensor characterization measurements during the manufacturing testing phase, storing the results (resonant frequency, quality factor, gain) in non-volatile memory. This preliminary action captures the unique parameters of each sensor without requiring complex real-time measurement systems during deployment, thus maintaining accuracy while reducing operational complexity.
Solution Approach 2:
The patent creates a digital copy of the sensor's physical characteristics by measuring its electrical response and storing the parameters in non-volatile memory. This digital model allows the system to compensate for manufacturing variations without physically modifying the sensor or requiring complex real-time measurement equipment, thereby reducing device complexity.
3Measurement precision
If equalization filter coefficients are stored in non-volatile memory, then signal accuracy is improved, but memory capacity requirements and device complexity increase
Solution Approach 1:
The patent changes the approach by storing only the essential sensor parameters (resonant frequency, quality factor, gain) rather than storing complete equalization filter coefficients. This parameter-based storage approach significantly reduces memory requirements while still enabling accurate signal equalization through subsequent coefficient computation.
Solution Approach 2:
The patent extracts only the critical sensor characteristics from the full characterization data and stores these condensed parameters in non-volatile memory. By taking out only the essential information (resonant frequency, quality factor, gain) rather than all possible measurement data, the system achieves signal accuracy with minimal memory capacity.
4Device complexity
If manufacturing variations are not compensated, then device complexity is reduced, but signal consistency and performance reliability deteriorate
Solution Approach 1:
The patent performs sensor characterization and stores parameters during manufacturing, then uses these pre-computed values to generate equalization filter coefficients that are applied during operation. This preliminary preparation enables performance consistency across production batches without requiring complex real-time adjustment mechanisms, thus maintaining reliability while controlling complexity.
Solution Approach 2:
The patent implements a feedback mechanism where measured sensor parameters are used to compute equalization coefficients that compensate for manufacturing variations. This feedback loop ensures performance consistency by continuously adjusting the signal processing based on the actual sensor characteristics, thereby improving reliability without excessive complexity.
Data Source
AI summary
Apparatus and methods for equalizing microelectromechanical systems (MEMS) sensors are disclosed. In certain embodiments, measured sensor parameters of a MEMS sensor are stored in a non-volatile memory (NVM) of a sensor signal processor used to process a sensor output signal of the MEMS sensor. The measured sensor parameters are retrieved by a digital signal processor (DSP) and used for equalizing sensor data provided to the DSP by the sensor signal processor during operation. The measured sensor parameters can be determined at test, per individual part, by measurements of the MEMS sensor's characteristics, and thus equalize the MEMS sensor while accounting for manufacturing and/or processing variations.