Beacon Signal Graph Matching for Indoor Positioning
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Solution Overview
Problem
Beacon-based radio frequency systems face instability due to environmental and hardware factors, leading to poor accuracy in object identification, particularly in indoor navigation and positioning applications.
Innovation Solution
A graphical near-field identification method that filters beacon signals based on preset conditions, matches them with beacon graphs, and uses RSSI values to estimate distance and determine object position, reconstructing the signal source graph for accurate region identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If RSSI-based ranging is used for beacon signal identification, then object positioning can be achieved, but the accuracy deteriorates due to signal instability from environmental and hardware factors
Solution Approach 1:
The patent segments the beacon signal identification process into multiple independent components: signal filtering module, graph matching module, and position estimation module. By dividing the system into discrete functional segments, each can be optimized independently to handle signal instability, improving overall measurement precision while maintaining reliability.
Solution Approach 2:
The patent applies preliminary filtering actions to beacon signals before they are used for positioning. The filtering module pre-processes signals by removing outliers and applying quality thresholds, ensuring that only reliable signals proceed to the positioning algorithm. This preliminary action prevents unstable signals from degrading measurement accuracy.
2Measurement precision
If multiple beacon signals are processed to improve positioning accuracy, then identification precision improves, but system complexity increases due to signal filtering, matching, and reconstruction processes
Solution Approach 1:
The patent implements dynamic signal processing where the system adapts its filtering and matching operations based on signal quality metrics. The filtering thresholds and matching criteria are dynamically adjusted according to environmental conditions, allowing the system to maintain high positioning accuracy while reducing unnecessary processing complexity in stable signal environments.
Solution Approach 2:
The patent changes key parameters such as signal strength thresholds, filtering window sizes, and graph matching criteria to optimize the balance between precision and complexity. By dynamically adjusting these parameters based on signal conditions, the system achieves high positioning accuracy without requiring overly complex processing for all scenarios.
3Reliability
If signal filtering and graph matching are applied to reduce environmental interference, then positioning reliability improves, but processing time increases
Solution Approach 1:
The patent applies partial filtering and matching operations based on signal quality assessments. For high-quality signals, minimal filtering is applied to reduce processing time, while only necessary graph matching operations are performed. This selective application of processing actions maintains positioning reliability while minimizing unnecessary time consumption.
Solution Approach 2:
The patent implements a skip mechanism where obviously valid signals are rapidly processed through simplified pathways, skipping detailed filtering and matching steps. This allows the system to quickly process reliable signals while applying comprehensive processing only when needed, thereby reducing overall processing time while maintaining positioning reliability.
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
This method reduces the impact of signal source instability and environmental interference, enabling quick and accurate object positioning by filtering and reconstructing beacon signals, thereby improving identification efficiency and accuracy.
Implementation Method 1
The main principle of the beacon is to transmit radio frequency in a specified channel, including data packets, which are obtained by the receiver and then analyzed and processed accordingly
Implementation Method 2
estimating a distance to the beacon by using a RSSI value of the beacon signal
Data Source
AI summary
A graphical near-field identification method and apparatus are provided. The method includes filtering a searched beacon signal according to a preset filtration condition. The method further includes matching a filtered beacon with beacons in all beacon graphs to obtain a beacon graph having a largest beacon matching number and the number of beacons matched with the beacon graph. The method further includes determining whether the number of the beacons matched with the beacon graph is less than a beacon determination minimum number requirement. The method further includes determining whether the number of the beacons matched with the beacon graph meets a beacon graph benchmark number condition. The method further includes determining that an object position is in a scenario where the beacon graph is located. The method further includes estimating a distance to the beacon by using a RSSI value of the beacon signal.