Gyroscope Sensitivity Calibration via Accelerometer Reference
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Solution Overview
Problem
MEMS-based sensors in portable devices, such as gyroscopes, suffer from bias and sensitivity errors due to environmental changes and mechanical stress, leading to inaccurate data that complicates sensor fusion and affects the precision of motion and orientation calculations.
Innovation Solution
A method for calibrating gyroscope sensitivity in portable devices using other sensor information, such as accelerometer data, by determining a reference orientation and comparing it to estimated orientations derived from gyroscope data with candidate sensitivity values to derive a calibrated sensitivity value, which reduces user involvement and energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration methods are used, then measurement precision can be improved, but user involvement and energy consumption increase
Solution Approach 1:
The system performs calibration automatically using sensor fusion between accelerometer and gyroscope without requiring user intervention. The processor autonomously determines reference orientations from accelerometer data and compares them with gyroscope-based estimated orientations to compute calibrated sensitivity values, making the calibration process self-executing and eliminating the need for manual user participation.
Solution Approach 2:
The calibration process is performed in advance during device operation without interrupting the user. The system continuously monitors sensor data and executes calibration routines during appropriate periods, preparing the gyroscope sensitivity values before they are needed for final computations, thus maintaining user convenience while ensuring measurement precision.
2Measurement precision
If calibration operations are performed frequently, then measurement precision improves, but energy consumption and computational load increase
Solution Approach 1:
The system performs calibration periodically rather than continuously, monitoring device motion patterns to identify appropriate calibration periods. The processor executes calibration routines during periods of low device usage or specific motion conditions, reducing overall computational load while maintaining measurement precision through timely updates of sensitivity values.
Solution Approach 2:
The calibration frequency and intensity are dynamically adjusted based on real-time device conditions and usage patterns. The system adapts the calibration process to actual needs, performing more frequent calibration when device motion patterns indicate opportunity and reducing frequency during stable periods, thereby optimizing the balance between precision and energy consumption.
3Measurement precision
If manual calibration is required, then measurement precision can be ensured, but device complexity and operation time increase
Solution Approach 1:
The calibration process is completely automated with no manual steps required. The processor autonomously collects sensor data from accelerometer and gyroscope, processes the information through sensor fusion algorithms, and computes calibrated sensitivity values without user intervention, eliminating the time loss associated with manual calibration procedures while maintaining measurement precision.
Data Source
AI summary
Systems and devices are disclosed for calibration of gyroscope sensitivity. By comparing a reference orientation determined without gyroscope data to estimated orientations determined with gyroscope data, a calibrated sensitivity value may be derived using a known relationship between a reference orientation and estimated orientations difference and gyroscope sensitivity.