Electronic Compass Calibration via Dynamic Magnetic Interference Data Selection
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Solution Overview
Problem
Current compass calibration methods face inefficiencies due to fixed selection of magnetic field data, leading to inaccurate sphere center coordinates and increased calculation power consumption, especially in environments with severe magnetic field interference.
Innovation Solution
A method to dynamically determine the target number of magnetic field data based on the interference level, allowing for flexible data selection during spherical magnetic field fitting to improve calibration accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fixed selection of magnetic field data is used for calibration, then the calibration process is simple, but the accuracy of sphere center coordinate is low and calculation power consumption is high
Solution Approach 1:
The patent applies dynamics by making the number of magnetic field data points flexible rather than fixed. The system dynamically adjusts the quantity of data used for spherical magnetic field fitting based on the detected interference level. When interference is severe, more data points are selected to improve accuracy; when interference is mild, fewer points are used to reduce calculation load. This dynamic adaptation resolves the contradiction between accuracy and power consumption.
Solution Approach 2:
The patent changes the parameter of data quantity based on interference conditions. By detecting the magnetic field interference level and adjusting the number of data points accordingly, the system optimizes the balance between calibration accuracy and computational energy consumption. This parameter adaptation allows the system to achieve high accuracy when needed while conserving energy when conditions permit.
2Measurement precision
If more magnetic field data is selected for fitting, then the accuracy of sphere center coordinate is improved, but the calculation power consumption increases
Solution Approach 1:
The system dynamically adjusts the number of data points based on real-time interference detection. Instead of always using a fixed large dataset, the system adapts the data quantity to the actual environmental conditions, achieving high accuracy when interference is severe while maintaining efficiency when conditions are favorable.
Solution Approach 2:
The patent changes the parameter of data quantity according to interference level. This parameter adaptation enables the system to optimize the trade-off between calibration accuracy and efficiency, using more data only when necessary to overcome severe interference while conserving computational resources during normal conditions.
3Measurement precision
If fixed number of magnetic field data is used for calibration, then the calculation process is fast, but the accuracy is influenced by data selection
Solution Approach 1:
The patent introduces a dynamic data selection mechanism that automatically adjusts the number of data points based on detected interference levels. This dynamic approach simplifies the overall process by eliminating manual data selection complexity while maintaining high accuracy through adaptive data quantity adjustment.
Solution Approach 2:
The system performs self-service by automatically detecting interference conditions and selecting appropriate data quantities without external intervention. The calibration process autonomously adapts to environmental conditions, reducing the complexity of data selection while ensuring accurate results through intelligent self-adjustment.
4Measurement precision
If dynamic adjustment of data number based on interference level is implemented, then the accuracy and efficiency are improved, but the calibration process complexity increases
Solution Approach 1:
The patent implements preliminary action by first detecting the magnetic field interference level before proceeding with calibration. This preliminary detection step enables the system to pre-determine the appropriate data quantity, simplifying the subsequent calibration process by eliminating the need for complex real-time adjustments during fitting.
Solution Approach 2:
The system uses feedback by detecting interference conditions and using this information to adjust data selection. The feedback mechanism creates a closed-loop control system that automatically optimizes calibration parameters based on environmental conditions, improving accuracy and efficiency while managing complexity through systematic feedback-based adjustment.
Data Source
AI summary
A calibration method for an electronic compass includes: acquiring an initial sphere center coordinate of a current calibration; acquiring a preset number of magnetic field data collected by a magnetic sensor; determining a target magnetic field interference level of an environment according to the preset number of magnetic field data and the initial sphere center coordinate; determining a target number of the magnetic field data according to the target magnetic field interference level; and performing spherical magnetic field fitting according to the target number of magnetic field data to calibrate the electronic compass.