Magnetometer Interference Detection via Sensor Fusion
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Solution Overview
Problem
Magnetometers in mobile devices face challenges in accurately measuring magnetic fields due to internal and external interference, leading to the need for recalibration, which can be resource-intensive and often unnecessary, especially when dealing with transient interference sources.
Innovation Solution
A method that utilizes non-magnetometer sensors like accelerometers and gyroscopes to differentiate between internal and external interference, deferring recalibration until persistent interference is confirmed, and prompting users to move away from transient interference sources, thereby optimizing recalibration and reducing resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If recalibration is performed frequently to maintain magnetometer accuracy, then measurement precision is improved, but use of energy and computing resources increases
Solution Approach 1:
The system continuously monitors magnetometer sensor data and compares expected motion data (computed from magnetometer readings) with reference data (from non-magnetometer sensors) to detect interference conditions. This feedback mechanism triggers recalibration only when interference is detected, avoiding unnecessary recalibrations and conserving energy resources while maintaining measurement accuracy.
Solution Approach 2:
The system changes the operational parameters of the magnetometer by switching between calibrated and uncalibrated states based on detected interference conditions. When interference is detected through comparison of expected and reference motion data, the system adjusts its operation by deferring or cancelling recalibration, thereby optimizing resource usage while maintaining measurement precision under normal conditions.
2Measurement precision
If recalibration is performed immediately when interference is detected, then measurement precision is improved, but loss of time increases due to unnecessary recalibrations
Solution Approach 1:
The system uses feedback from multiple sensor sources (magnetometer, accelerometer, gyroscope) to verify interference conditions before triggering recalibration. By comparing expected motion data with reference data over time intervals, the system confirms persistent interference before initiating recalibration, avoiding time loss from unnecessary recalibrations caused by transient interference.
Solution Approach 2:
The system performs preliminary detection and verification of interference conditions by monitoring sensor data over specified time intervals and comparing expected versus reference motion data. This preliminary action confirms whether interference is persistent before committing to recalibration, thereby avoiding unnecessary time expenditure on transient interference events.
3Reliability
If multiple sensors are used to detect interference, then reliability of interference detection is improved, but device complexity increases
Solution Approach 1:
The system uses non-magnetometer sensors (accelerometer, gyroscope) that serve multiple functions: they provide reference motion data for interference detection, contributes to expected motion computation, and help distinguish between device motion and magnetic interference. This multi-functionality improves detection reliability without significantly increasing overall device complexity.
Solution Approach 2:
The system uses non-magnetometer sensors as intermediaries to indirectly detect magnetic interference. Instead of directly measuring magnetic field disturbances, the system uses accelerometer and gyroscope data as mediators to infer interference conditions by comparing expected versus actual motion, thereby improving detection reliability through a sophisticated but manageable sensor integration approach.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy and efficiency of magnetometer data by minimizing unnecessary recalibrations, conserving computing and power resources, and improving user experience by reducing the frequency of recalibration prompts.
Implementation Method 1
monitoring magnetometer sensor data generated by a magnetometer
Data Source
AI summary
Methods and apparatus employing non-magnetometer navigational sensor data to assist in determining whether a change in a magnetic field detected by a magnetometer is likely due to a source of internal or external magnetic interference, and more generally, whether such interference is likely to be persistent or transient. If the magnetic field data detected by the magnetometer indicates a large change in magnetic field, but the non-magnetometer navigational sensor (e.g., gyroscope) data does not indicate a corresponding change in orientation of the mobile device contemporaneous with the change in magnetic field, then the cause of the magnetic field change may be determined as likely originating from a localized external interference source and the device may prompt the user to move away from the interference source, rather than initiating a recalibration of the magnetometer.