Yaw Rate Sensor Offset Calibration Using Adaptive Idle-State Filtering
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Solution Overview
Problem
Conventional methods for calibrating rotation rate sensor offsets are difficult and expensive to implement, and often fail to provide efficient offset correction in various utilization environments, such as smartphones and wearables, due to production-related systematic errors and noise from slight movements.
Innovation Solution
A method that adapts filter parameters to the idle-state conditions of the rotation rate sensor, allowing for different filtering times and more precise offset correction by determining the sensor's idle state through estimated average and variance calculations, and using exponential smoothing to adjust the sensor values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional offset calibration methods are used, then offset correction can be achieved, but the implementation becomes difficult and expensive requiring multiple sensor types
Solution Approach 1:
The patent extracts and eliminates the requirement for additional sensor types (acceleration sensors, magnetometers) by using only the rotation rate sensor's own data. The solution takes out the dependency on external sensors and implements calibration using solely the rotation rate sensor's measured values, statistical properties, and idle state detection capabilities.
Solution Approach 2:
The rotation rate sensor performs its own offset calibration using its own measured values without requiring external assistance from other sensor types. The system uses the sensor's idle state periods and statistical analysis of its own data to determine and apply offset corrections autonomously.
2Adaptability or versatility
If fixed filtering time is used for offset calibration, then the calibration process is simple, but it cannot adapt to different utilization environments and noise levels
Solution Approach 1:
The patent implements dynamic adaptation by detecting the idle state of the rotation rate sensor and adjusting the filtering time accordingly. Instead of a fixed filtering time, the system dynamically determines the appropriate filtering duration based on whether the sensor is in idle state, allowing adaptation to different utilization environments while maintaining a relatively simple calibration process.
Solution Approach 2:
The filtering time parameter is changed dynamically based on the detected idle state conditions. The system modifies this critical parameter according to the sensor's operational context, enabling the calibration process to adapt to different environments (such as smartphone vs. wearable applications) without requiring completely different calibration algorithms.
3Measurement precision
If longer filtering time is used for noisy sensors, then offset correction precision improves, but the calibration time increases
Solution Approach 1:
The patent employs feedback mechanisms by continuously monitoring the idle state detection results and statistical properties of the rotation rate sensor data. This feedback allows the system to determine when sufficient calibration data has been collected and when the filtering process can be terminated, optimizing the balance between precision and calibration time.
Solution Approach 2:
The system applies partial action by using only the necessary amount of filtering time required to achieve adequate offset correction precision. Instead of always applying maximum filtering duration, the system adjusts the filtering time to be sufficient but not excessive, particularly during idle state periods when the sensor provides stable data for calibration.
Data Source
AI summary
A method for offset calibration of a rotation rate sensor signal of a rotation rate sensor. In a first step, an ascertainment is made that the rotation rate sensor is in an idle state. In a second step, after the first step, a filter parameter is determined as a function of the measured rotation rate sensor values, measured in the idle state, of the rotation rate sensor. In a third step, after the second step, a filtered measured rotation rate sensor value is determined with the aid of the filter parameter. An offset is determined with the aid of the filtered measured rotation rate sensor value.