Fingerprinting Positioning Database Clustering for Search Optimization
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Solution Overview
Problem
Conventional fingerprinting positioning methods require large database capacity and long search times, especially as the service area expands, leading to imprecise and time-consuming location estimation.
Innovation Solution
A method for building a database that clusters sample points by received signal strengths (RSS) for access points, generating a cluster table, and using this table to determine a search region for location estimation, thereby reducing database volume and improving estimation precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the service area is widened to cover larger regions, then the coverage range is improved, but the database capacity requirement increases and search time increases
Solution Approach 1:
The patent divides the service area into multiple regions based on clustering sample points according to their spatial coordinates and RSS characteristics. Each region is stored as a separate entry in the database with its own set of sample points and corresponding RSS values. This segmentation allows the system to handle large service areas by storing data in manageable, organized chunks rather than a single large database, thereby reducing the effective database capacity requirement for each query while maintaining comprehensive coverage.
Solution Approach 2:
The patent creates different database entries for different regions, each containing RSS data specific to that local area. This allows the system to use locally relevant RSS information for positioning queries within each region, improving positioning accuracy while reducing the overall database size that needs to be searched. Each region's database entry is optimized for its specific spatial characteristics rather than using a uniform large-scale database.
2Area of stationary object
If the database is expanded to cover larger service areas, then the coverage range is improved, but the search time increases
Solution Approach 1:
By segmenting the service area into multiple regions with separate database entries, the patent reduces the search time for positioning queries. Instead of searching through a large single database, the system only searches within the relevant regional database entry corresponding to the user's location. This segmentation dramatically reduces the search space and time required for location estimation while maintaining comprehensive service coverage.
Solution Approach 2:
The patent performs preliminary clustering of sample points into regions during database construction, organizing data into a hierarchical structure with region-level summaries and detailed sample point information. This preliminary organization allows the system to quickly identify which regional database entry is relevant for a given query without searching the entire database, thereby reducing search time while maintaining extensive service area coverage.
3Measurement precision
If more sample points are stored in the database, then the positioning precision is improved, but the database volume increases
Solution Approach 1:
The patent segments sample points into regional groups based on their spatial distribution and RSS characteristics. Each region stores only the sample points relevant to that specific area, rather than storing all sample points in a single large database. This segmentation maintains positioning precision within each region by preserving all necessary local sample data while reducing the overall database volume by eliminating redundant sample points from regions where they are not needed.
Solution Approach 2:
The patent creates region-specific database entries that contain only the sample points and RSS data relevant to each local area. This local quality approach ensures that positioning precision is maintained within each region by preserving all necessary local measurements, while the overall database volume is reduced because each region only stores its relevant sample points rather than duplicates from other regions.
4Area of stationary object
If the search range is widened to cover more areas, then the coverage is improved, but the processing speed decreases
Solution Approach 1:
The patent segments the search range into multiple regional entries, each containing positioning data for a specific area. When a positioning query is performed, the system first determines which regional entry corresponds to the user's location and then processes only that specific region. This segmentation maintains comprehensive coverage by having multiple regional entries while improving processing speed by limiting the search to only the relevant region rather than the entire service area.
Solution Approach 2:
The patent performs preliminary organization of sample points into regional clusters during database construction, creating a hierarchical database structure with region identifiers and sample point mappings. This preliminary action enables the system to quickly identify and access only the relevant regional data for each query, maintaining wide coverage through multiple regional entries while significantly improving processing speed by avoiding unnecessary search across the entire service area.
Data Source
AI summary
A method for building a database for fingerprinting positioning including: generating, by a database building device, raw data by collecting received signal strengths (RSSs) for access points (APs) at each sample point (SP); and generating a cluster table by clustering SPs for each of the APs according to the RSS for the AP, using the generated raw data.