Magnetometer Heading Bias Correction via Image Road Feature Alignment
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Solution Overview
Problem
Existing systems for estimating the position and orientation of electronic devices, such as smartphones and wearables, face challenges in accurately determining heading due to biases in magnetometer readings, especially when used in conjunction with GNSS and image sensors, leading to inconsistencies in augmented reality applications.
Innovation Solution
The system employs a combination of GNSS, image sensors, and magnetometers to correlate image data with mapping data, determining a bias in magnetometer output, and adjusts the magnetometer readings to improve heading estimation by aligning road features in images with known pathways, thereby enhancing the accuracy of device orientation and position estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If magnetometer readings are used to determine heading, then device orientation can be estimated, but biases in magnetometer readings lead to inaccurate heading estimates
Solution Approach 1:
The system captures images with the device camera, detects road features (lines, vanishing points) in the images, and uses these visual observations to compute a corrected heading. This visual feedback loop continuously adjusts and corrects the magnetometer-based heading estimates, eliminating biases without requiring manual calibration or external reference systems.
Solution Approach 2:
The patent introduces image data and road feature detection as an intermediary between the magnetometer and the final heading estimate. Instead of directly trusting magnetometer readings, the system uses visual detection of road geometry as a mediator to indirectly determine the device's heading, thereby bypassing magnetometer biases.
2Measurement precision
If multiple sensors (GNSS, image sensors, magnetometers) are combined to improve position and orientation estimation, then accuracy can be enhanced, but system complexity increases
Solution Approach 1:
The device's existing camera, originally designed for general imaging purposes, is repurposed to perform specific functions: detecting road lines, identifying vanishing points, and calculating heading. This multi-functional use of the camera eliminates the need for dedicated sensors for these tasks, reducing overall system complexity while maintaining multi-sensor integration benefits.
Solution Approach 2:
The system uses the device's own camera and processing capabilities to self-calibrate and self-correct its sensor readings. By detecting road features in the environment and using geometric relationships, the device autonomously computes corrections for its magnetometer and GNSS data without requiring external calibration equipment or complex manual setup.
Data Source
AI summary
A device implementing a system for estimating device orientation includes at least one processor configured to obtain a first estimate for a heading of a device, the first estimate being based on output from a magnetometer of the device. The at least one processor is further configured to capture image data using an image sensor of the device, and determine at least one second estimate of the heading based on correlating the image data with mapping data. The at least one processor is further configured to determine a bias associated with output of the magnetometer based on the first estimate and the at least one second estimate, and adjusting output of the magnetometer based on the determined bias.