Error Radius Lookup for Indoor Location Accuracy
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Solution Overview
Problem
Location estimation techniques, such as Wi-Fi positioning systems, face inaccuracies due to signal fluctuations, leading to errors in determining the position of mobile devices, especially indoors where GPS data is not readily available.
Innovation Solution
A data structure is created that maps an error radius to a scaled geographic area, allowing for rapid lookup of the corresponding error radius for an inferred position based on beacon observations, using a correlation between errors in training and test datasets to establish accurate error radii for each scaled area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If Wi-Fi positioning systems are used to determine location indoors, then location information can be provided where GPS is unavailable, but signal fluctuations cause increased errors and inaccuracies in position determination
Solution Approach 1:
The patent pre-calculates error radii for multiple scaled geographic areas before runtime based on training data, storing these values in a data structure. When positioning is needed, the system simply looks up the pre-computed error radius corresponding to the inferred position's scaled area, avoiding real-time complex calculations and providing immediate accuracy assessment.
Solution Approach 2:
The patent transforms the continuous error measurement problem into a discrete lookup problem by dividing the geographic space into scaled areas and assigning representative error radii to each. This parameter transformation from continuous to discrete space enables rapid determination of accuracy metrics without real-time signal analysis.
2Measurement precision
If error radius calculation is performed in real-time for each position, then accurate error radii are provided, but computational complexity and processing time increase
Solution Approach 1:
The system performs error radius calculations during an offline training phase, storing results in a data structure organized by scaled geographic areas. During actual positioning operations, the system only needs to perform a simple lookup operation to retrieve the pre-computed error radius, dramatically reducing processing time while maintaining accuracy.
Solution Approach 2:
The patent divides the geographic space into multiple scaled areas with different levels of detail. Each scaled area has its own pre-computed error radius stored in the data structure. This segmentation allows the system to handle different spatial resolutions efficiently, providing accurate error radii without uniform high-computation overhead across all locations.
3Measurement precision
If detailed scaled geographic areas are used to map error radii, then accurate error determination is achieved, but data structure complexity and memory requirements increase
Solution Approach 1:
The patent creates a unified data structure that handles multiple scaled geographic areas with different resolutions using a single organization scheme. The same data structure format and lookup process works across all scaled areas, from coarse to fine granularity, simplifying implementation despite the diversity of spatial resolutions.
Solution Approach 2:
The system assigns different levels of detail to different geographic areas based on their scaled area classification. Each scaled area receives an error radius appropriate to its level of detail, with more granular areas potentially having more precise error measurements. This local adaptation optimizes both accuracy and data efficiency.
Data Source
AI summary
A system and method determining an error radius reflecting the accuracy of a calculated position of a processing device is provided. A data structure includes an error radius mapped to a scaled geographic area or “tile” comprising an area in which a calculated position may be determined. The data structure may include a plurality of first fields identifying a scaled geographic area based on a global projection reference system, and a plurality of second fields identifying, for each of the first fields, a position error radius associated with a scaled geographic area and level. For any calculation of an inferred position based on beacon observations, a rapid lookup of the corresponding scaled area including the new inferred position in the data structure returns an error radius for the new inferred position.