Indoor Positioning Fingerprint Search Using Predicted Location Range
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Solution Overview
Problem
Fingerprint-based methods for determining the location of mobile terminals in indoor spaces require significant processing time and cost due to repeated similarity searches in large positioning databases, leading to inefficiencies and potential errors.
Innovation Solution
A method and apparatus that utilize a mobile terminal's surrounding positioning resource information and movement state data to limit the similarity search range within a positioning database, selecting a predicted location range based on previous location information and movement data to determine the current location with improved accuracy and speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fingerprint-based methods perform repeated similarity search in the entire positioning database to continuously determine location, then location determination accuracy is maintained, but processing time and computational cost increase significantly
Solution Approach 1:
The patent divides the entire positioning database into multiple clusters based on spatial relationships and characteristics of positioning resources. Instead of performing similarity search across the whole database, the system performs search only within the relevant cluster corresponding to the terminal's current location area, significantly reducing the search space while maintaining accuracy.
Solution Approach 2:
The patent applies different processing strategies to different parts of the database. High-accuracy similarity search is performed locally within relevant clusters where the terminal is likely to be located, while other parts of the database are excluded from search. This localized approach maintains accuracy where needed while reducing overall computational burden.
2Measurement precision
If fingerprint-based methods perform repeated similarity search in the entire positioning database to continuously determine location, then location determination accuracy is maintained, but processing cost increases significantly
Solution Approach 1:
The positioning database is segmented into multiple clusters based on spatial and resource characteristics. The system identifies and searches only the relevant cluster corresponding to the terminal's location area, reducing the number of comparisons required and improving processing efficiency while maintaining accuracy through focused local search.
Solution Approach 2:
The system pre-processes the positioning database by clustering reference points and organizing them spatially before actual location determination. This preliminary organization enables rapid identification of relevant search areas during continuous tracking, avoiding the need to scan the entire database repeatedly and thus improving processing efficiency.
3Loss of time
If the search range is limited to a predicted location range based on movement state information, then processing time and computational load are reduced, but location determination accuracy may be affected
Solution Approach 1:
The system dynamically adjusts the search range based on the terminal's movement state information. When the terminal is stationary or moving slowly, a smaller search range is used. When movement is detected, the search range is expanded appropriately. This dynamic adaptation ensures that the search always covers the actual location area while minimizing unnecessary computations, thus maintaining accuracy while reducing processing time.
Solution Approach 2:
The patent changes the search parameter (search range) based on movement state parameters. By adjusting the spatial extent of the search area according to detected movement, the system optimizes the balance between search completeness and computational efficiency, ensuring accurate location determination with reduced processing requirements.
Data Source
AI summary
Disclosed is an apparatus for providing a service, which includes a communication module, a positioning database (DB) configured to store a plurality of information about positioning resources observable at each of a plurality of reference points within a target area, and a processor functionally connected to the communication module and the positioning DB, wherein the processor is configured to acquire surrounding positioning resource information and movement state information of a mobile terminal through the communication module, select several points within a predicted location range of the mobile terminal from the plurality of reference points based on previous location information and the movement state information of the mobile terminal, and determine a location with a highest similarity to the acquired positioning resource information among the several points as a current location of the mobile terminal.