Inertial Sensor Self-Calibration via Rotational Motion
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Solution Overview
Problem
Inertial sensing systems face significant errors due to scale-factor and bias issues, particularly in dynamic environments, which affect navigation and measurement accuracy.
Innovation Solution
An inertial system with a calibration system that continuously measures inertial parameters by rotating sensors through multiple orientations, using a motion controller and Kalman filter to cancel bias errors in real-time, allowing for continuous self-calibration during operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional inertial sensors are used without continuous calibration, then the system structure remains simple, but measurement precision deteriorates due to bias errors and scale-factor errors
Solution Approach 1:
The inertial system performs self-calibration by utilizing its own sensor outputs and a motion controller to automatically detect and correct bias errors and scale-factor errors without requiring external calibration equipment or redundant sensors, thereby maintaining measurement precision while avoiding increased system complexity
Solution Approach 2:
The system dynamically adjusts calibration parameters (bias values and scale-factor values) based on real-time sensor measurements and motion states, allowing the inertial system to adapt to changing conditions and maintain accuracy without adding physical complexity to the device structure
2Measurement precision
If redundant sensors are added to mitigate bias errors, then measurement precision improves, but device complexity and cost increase
Solution Approach 1:
Instead of using redundant sensors to detect and correct errors, the system uses a single inertial sensor system that automatically calibrates itself by analyzing its own output signals during known motion states, eliminating the need for additional sensors while maintaining the ability to mitigate bias errors
Solution Approach 2:
The system implements a feedback mechanism where sensor outputs are continuously monitored, compared against expected values during calibration motions, and used to automatically adjust calibration parameters, thereby achieving error mitigation through intelligent processing rather than hardware redundancy
3Productivity
If calibration is performed periodically rather than continuously, then productivity improves by reducing calibration time, but measurement precision deteriorates in dynamic environments
Solution Approach 1:
The inertial system performs calibration continuously during normal operation by integrating calibration motions into the operational sequence, allowing calibration to occur without interrupting productivity while maintaining measurement precision in dynamic environments through real-time parameter updates
Solution Approach 2:
The calibration process is made dynamic and adaptive, automatically adjusting calibration activities based on the operational state and motion characteristics of the system, allowing calibration to occur continuously during operation rather than requiring periodic interruptions, thus maintaining both productivity and precision
Data Source
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AI summary
One embodiment of the invention includes an inertial system. The system includes at least one inertial sensor configured to measure an inertial parameter associated with each of at least one axis. The system also includes a calibration system configured to sequentially measure an inertial calibration parameter at each of a plurality input axes. The system further includes an inertial processor configured to calculate motion of the inertial system based on the inertial parameter associated with each of the respective at least one axis and the sequential measurements of the inertial calibration parameter at each of the plurality of input axes.