Multi-Position Beacon Positioning System
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Solution Overview
Problem
Existing positioning systems rely on a single 'best' location for beacons, which can be inaccurate for mobile or relocated beacons, hindering precise location determination of electronic devices.
Innovation Solution
The system maintains multiple locations for each beacon in a database, each associated with a probability, and uses these to estimate the location of electronic devices by clustering observations and calculating probabilities, allowing for more accurate location determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single 'best' location is maintained for each beacon, then the database structure is simple and location lookup is fast, but location accuracy deteriorates when beacons are mobile or relocated
Solution Approach 1:
The patent segments the single location concept into multiple discrete locations, each with its own probability weight. Instead of storing one location per beacon, the system stores multiple locations (location1, location2, ..., locationN) with corresponding probabilities (p1, p2, ..., pN), allowing the beacon to represent multiple possible positions simultaneously.
Solution Approach 2:
The patent introduces dynamics by making the beacon location probabilistic rather than static. The system continuously updates location probabilities based on observed signals, allowing the 'best' location to change over time as new observations are made. This dynamic adaptation enables the system to track mobile beacons effectively.
2Reliability
If multiple locations are maintained for beacons, then location accuracy for mobile beacons improves, but system complexity and computational requirements increase
Solution Approach 1:
The patent changes the parameter representation from a single location coordinate to a set of parameters including multiple locations, probability weights, and signal strength measurements. This parameter expansion allows the system to capture the uncertainty and mobility of beacons while providing a structured framework for processing.
Solution Approach 2:
The patent replaces the traditional geometric/trigonometric positioning mechanics with a probabilistic information-processing approach. Instead of relying solely on signal strength attenuation models and geometric intersections, the system uses probability theory to fuse multiple observations and determine beacon locations, making the system more robust to mobility and environmental variations.
3Measurement precision
If a single location is used for beacon positioning, then the positioning algorithm is computationally efficient, but precision in determining electronic device location deteriorates
Solution Approach 1:
The patent performs preliminary actions by pre-calculating and maintaining multiple beacon locations and their probabilities in the database before actual positioning is needed. When a positioning request occurs, the system can quickly retrieve these pre-computed locations and use them directly, reducing the computational burden during the actual positioning operation.
Solution Approach 2:
The patent maintains continuous updates of beacon locations and probabilities through ongoing signal observations and probability recalculations. This continuous action ensures that the positioning system always has current, accurate beacon location information available, improving electronic device positioning precision without requiring intensive computation at the moment of positioning.
Data Source
AI summary
In various embodiments, techniques are provided for determining and associating multiple locations with beacons, and estimating a location of an electronic device based on beacons having multiple associated locations.