Field Sensor Error Correction Using Angular Rate Data
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Solution Overview
Problem
Existing methods for calibrating field sensors like magnetometers and accelerometers are inadequate for continuously determining and correcting sensor bias over time and varying conditions, requiring large movements or numerical integration, which are computationally intensive and limited in real-time calibration.
Innovation Solution
A system that uses angular rate data from a gyroscope to continuously estimate and correct sensor errors by relating it to field sensor measurements, allowing for periodic reevaluation and compensation of bias without extensive user interaction or specific movements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration methods (mean of max/min values or least squares sphere fitting) are used to determine sensor bias, then sensor bias can be estimated, but large movements (360 degree movement or figure-eight pattern) are required which are cumbersome and not suitable for continuous calibration
Solution Approach 1:
The patent replaces mechanical movement-based calibration (requiring physical 360-degree rotations or figure-eight patterns) with a computational approach using angular rate data from gyroscopes. Instead of relying on mechanical sensor movements to generate calibration data, the system uses gyroscope measurements of angular velocity combined with magnetic field measurements to calculate sensor bias through mathematical relationships, eliminating the need for cumbersome physical calibration movements.
2Measurement precision
If recalibration is performed to address sensor bias changes over time or operating conditions, then sensor accuracy can be maintained, but full recalibration is computationally intensive and time-consuming
Solution Approach 1:
The patent enables continuous sensor bias determination by processing angular rate data and magnetic field measurements in real-time as the device operates. Instead of periodic recalibration interrupts, the system continuously updates bias estimates using the relationship between gyroscope angular velocity measurements and magnetic field sensor outputs, maintaining accuracy without stopping normal device functionality.
Solution Approach 2:
The system uses feedback from gyroscope angular rate measurements to continuously adjust and update magnetic field sensor bias estimates. The angular velocity data provides real-time information about device orientation changes, which is fed back into the bias calculation algorithm to compensate for drift and environmental changes, creating a self-correcting calibration system.
3Measurement precision
If numerical integration of gyroscope data is used to calibrate compass bias, then bias can be determined, but the computational integration process is intensive particularly for systems without excess processing power
Solution Approach 1:
The patent extracts and utilizes the angular velocity information directly from gyroscope measurements without performing full numerical integration of gyroscope data. By using the angular rate data in conjunction with magnetic field measurements to directly calculate bias through mathematical relationships, the system obtains calibration accuracy comparable to integration methods while avoiding the computationally intensive integration process.
Data Source
AI summary
A system and method for determining errors and calibrating to correct errors associated with field sensors, including bias, scale, and orthogonality, includes receiving and providing to a processor angular rate data and a first field vector relative to a first reference directional field and a second field vector relative to a second reference field from at least one field sensor. The processor is configured to relate the first field vector and the second field vector to the angular rate data to determine an error of the at least one field sensor. The processor is also configured to identify a compensation for the error of the at lease one field sensor needed to correct the first field vector and the second field vector and repeat the preceding to identify changes in the error over time and compensate for the changes in the error over time.