Collaborative Magnetic Positioning for Fast Indoor Initialization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing magnetic-based indoor positioning technologies face challenges such as ambiguity in magnetic fingerprints, long initialization times in large venues, delays in reacquisition due to inertial sensor errors, and reduced accuracy in areas with low magnetic field variations, necessitating additional infrastructure for improvement.
Innovation Solution
A method and system for magnetic-based collaborative positioning that utilizes collaborative assistance from neighboring portable devices to enhance accuracy and reliability by sharing magnetic field measurements, motion data, and relative observations, eliminating the need for dedicated infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If magnetic-based positioning is used in large venues with low spatial variations, then coverage is improved, but initialization time increases and accuracy degrades
Solution Approach 1:
The system performs preliminary actions by using motion sensor data to predict the portable device's position before magnetic field measurement is completed. This prediction is made in advance based on dead reckoning from previously known positions, allowing the system to prepare expected position information while magnetic measurements are being taken, thereby reducing initialization time in large venues.
Solution Approach 2:
The system implements feedback by using collaborative assistance data from neighboring portable devices to continuously refine and correct position estimates. The neighboring devices provide feedback information about their positions and magnetic field characteristics, which helps resolve ambiguities and accelerates initialization even in areas with low spatial variations of the magnetic field.
2Area of stationary object
If magnetic-based positioning is used in large venues with low spatial variations, then coverage is improved, but positioning accuracy deteriorates
Solution Approach 1:
The system merges multiple data sources including magnetic field measurements, motion sensor data from inertial sensors, and collaborative assistance data from neighboring portable devices. By combining these different types of information, the system compensates for the low spatial variations in magnetic fields and maintains positioning accuracy across large coverage areas.
Solution Approach 2:
The system uses motion sensor data and collaborative assistance data as intermediary information to bridge gaps in magnetic field measurement precision. When magnetic field variations are low and direct positioning accuracy would deteriorate, these intermediary data sources provide additional constraints and information to maintain overall positioning accuracy.
3Reliability
If additional infrastructure is deployed to improve magnetic positioning accuracy, then positioning reliability is improved, but device complexity and cost increase
Solution Approach 1:
The system enables portable devices to serve themselves and each other for positioning purposes. Instead of requiring dedicated infrastructure, the portable devices use their own motion sensors, magnetometers, and communicate with neighboring devices to collectively achieve reliable positioning. This self-service approach maintains positioning reliability while avoiding additional infrastructure complexity.
Solution Approach 2:
The system makes portable devices multi-functional by using them not only for their primary purposes but also as positioning sensors and collaborators. The same portable devices that users carry for communication also perform magnetic field measurements, inertial sensing, and mutual assistance for positioning, eliminating the need for separate dedicated positioning infrastructure.
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
Improves positioning accuracy and reduces initialization times by leveraging collaborative data from neighboring devices, maintaining tracking in low magnetic field areas, and facilitating rapid reacquisition without additional infrastructure.
Implementation Method 1
a magnetometer outputting magnetic field measurements for the portable device
Data Source
AI summary
Magnetic-based collaborative positioning of a portable device involves obtaining magnetic field measurements for the portable device, obtaining magnetic fingerprint map information, obtaining parameters of motion of the portable device, obtaining collaborative assistance data from at least one neighbor portable device and determining position of the portable device based on the obtained magnetic field measurements, the obtained magnetic map information, the obtained motion parameters and the obtained collaborative assistance data.