Wireless Beacon Stability Analysis for Positioning Accuracy
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Solution Overview
Problem
Existing positioning systems using wireless communication devices as reference points face inaccuracies due to pathological beacons that move or exhibit unstable behaviors, leading to unreliable position estimates for client devices.
Innovation Solution
The method involves detecting and characterizing pathological beacon behaviors by analyzing temporal and spatial distributions of signal detection, clustering reference points, and determining aggregate stability values to identify and correct unstable beacons, thereby improving the reliability of position estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If wireless communication devices are used as reference points for positioning, then positioning coverage is expanded and time to first fix is reduced, but positioning reliability deteriorates due to mobile devices lacking fixed locations
Solution Approach 1:
The system performs preliminary analysis of beacon behavior patterns before using them for positioning. By analyzing temporal and spatial distributions of signals, clustering reference points, and determining aggregate stability values in advance, the system identifies and excludes unstable beacons from positioning calculations, thereby maintaining reliability while using wireless devices as reference points
Solution Approach 2:
The system continuously monitors and analyzes beacon behavior patterns, using feedback from signal detection data to refine the identification of stable versus unstable beacons. This feedback mechanism allows the system to adaptively determine which beacons should be excluded from positioning calculations based on their observed behavior characteristics
2Productivity
If all wireless devices are treated as stable reference points, then positioning speed is improved, but positioning accuracy deteriorates due to inclusion of mobile beacons
Solution Approach 1:
The system applies different treatment to different beacons based on their individual stability characteristics. By analyzing the local behavior patterns of each beacon (temporal distribution of signals, spatial distribution, cardinality of reference point sets), the system identifies which beacons exhibit stable versus mobile behavior and applies appropriate weighting or exclusion accordingly
Solution Approach 2:
The system segments the set of all wireless devices into stable beacons and mobile beacons based on analyzed behavior patterns. By dividing the reference point population into distinct groups with different stability characteristics, the system can process stable beacons for rapid positioning while excluding mobile beacons that would degrade accuracy
3Reliability
If statistical analysis of beacon behavior is performed, then identification of unstable beacons is improved, but system complexity increases
Solution Approach 1:
The system uses beacons themselves to provide the data needed for their classification. By having beacons transmit signals that are analyzed for temporal and spatial distribution patterns, the beacons essentially self-identify as stable or mobile through their own transmission behavior, eliminating the need for external monitoring infrastructure
Solution Approach 2:
The same signal detection infrastructure used for basic positioning also serves the dual purpose of analyzing beacon behavior patterns. The existing receivers and processors perform both positioning calculations and stability analysis using the same data streams, making the system multi-functional without requiring separate dedicated hardware
Data Source
AI summary
In one embodiment, a system determines a designated wireless device lacks a fixed geographic location, and uses the determination that the designated wireless device lacks a fixed geographic location to improve location estimates. The system determines one or more neighboring wireless devices have relationships with the designated wireless device, wherein a relationship is established when wireless signals from a neighboring wireless device and the designated wireless device are detected by a same receiver. A measure of likelihood is calculated that the designated wireless device lacks a fixed geographic location based at least in part on a number of the relationships or a duration of the relationships. Based on the measure of likelihood, the designated wireless device is excluded from being used in the wireless positioning system as a beacon for estimating the location of a client device.