Vector Sensor Self-Calibration Using Elliptical Fitting and DPI
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Solution Overview
Problem
Existing manual sensor calibration methods are labor-intensive, slow, and produce inconsistent results, necessitating improved automated solutions for vector sensor calibration.
Innovation Solution
A method for calibrating vector sensors using an elliptical-fitting method for attitude accelerometers, dot-product invariance for magnetometers, and chi squared distribution tests, combined with root mean square error analysis, to align sensor elements with Earth's gravitational and magnetic fields, eliminating the need for expensive external sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual sensor calibration methods are used, then calibration can be performed, but the process is labor-intensive and slow
Solution Approach 1:
The system performs self-calibration by automatically determining calibration parameters using the elliptical-fitting method and dot-product invariance method, eliminating the need for manual intervention. The sensor package autonomously processes calibration data and computes correction parameters, transforming a labor-intensive manual process into an automated self-service operation that significantly improves productivity while reducing labor intensity.
2Reliability
If manual sensor calibration methods are used, then calibration can be performed, but results are inconsistent
Solution Approach 1:
The patent replaces manual mechanical calibration operations with computational algorithms. The elliptical-fitting method and dot-product invariance method provide mathematically rigorous, repeatable calculations that eliminate human error and subjectivity. This substitution of mechanical/manual processes with automated computational methods ensures consistent, reliable calibration results while maintaining high efficiency through automated data processing.
3Ease of manufacture
If traditional calibration methods are used, then sensor calibration can be achieved, but expensive external sources are required
Solution Approach 1:
The patent introduces mathematical invariants (elliptical-fitting relationships and dot-product invariance) as intermediaries between the sensor package and the calibration process. These mathematical relationships serve as mediators that enable accurate calibration without requiring expensive external calibration sources. The invariants provide a bridge that allows the system to determine calibration parameters using only internal sensor measurements and known geometric relationships, thereby reducing costs while maintaining precision.
Data Source
AI summary
Methods, and systems of use, for sensor calibration. The method may comprise calibrating an attitude accelerometer of a sensor using an elliptical-fitting method, which may be based on calibration positions. The method may further calibrate a magnetometer of the sensor using a dot-product invariance (DPI) method, which may be based on the calibration positions. The method may comprise determining a magnetometer-calibration status of the magnetometer based on a chi squared distribution test method and a root mean square error (RMSE) method of dot-products generated by the DPI method. The method may further comprise calibrating an acoustic accelerometer of the sensor using the DPI method, which may be based on relative-values of a shape matrix. The method may comprise scaling an acoustic accelerometer of the sensor using a hydrophone. The system may comprise a sensor-error engine configured to perform steps of the disclosed methods.