Fingerprint Data Pre-Processing for Positioning Model Accuracy
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Solution Overview
Problem
Conventional fingerprint-style positioning systems face challenges in accurately collecting received signal strength (RSS) data due to time lags between position changes and RSS observations, leading to localized observation positions and reduced estimation accuracy.
Innovation Solution
A computer-implemented method that corrects mobile object positions using previous observation times and sets a time window to synchronize RSS changes with position changes, generating a uniform RSS distribution for improved positioning accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fingerprints are collected while surveyors walk along paths carrying collection devices, then data collection is efficient and covers large areas, but time lag occurs between position change and RSS change and observation positions become localized
Solution Approach 1:
The patent applies preliminary action by correcting the position information before it is used for fingerprint matching. Specifically, the system calculates corrected position information by referencing position data from a predetermined time period before the RSS measurement, thereby compensating for the time lag in advance and ensuring that the position data aligns with the actual measurement timing
Solution Approach 2:
The patent implements feedback by using the relationship between position changes and RSS changes to iteratively refine position correction. The system observes how RSS varies with position over time, uses this feedback to determine appropriate correction time periods, and continuously improves the accuracy of position alignment between measured and stored fingerprint data
2Measurement precision
If position correction using time window is applied, then position estimation accuracy increases, but processing complexity increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the time window parameter based on movement speed. The system determines the correction time period according to the detected movement speed of the mobile object, extending the time window for faster movements and using shorter windows for slower movements, thereby optimizing processing efficiency while maintaining accuracy
Solution Approach 2:
The patent segments the correction process into distinct functional modules: movement detection, time window determination, position correction calculation, and fingerprint matching. This segmentation allows each module to be optimized independently and facilitates efficient implementation through specialized processing for each task
3Ease of manufacture
If RSS distribution is non-uniform due to movement path localization, then data collection is simplified, but positioning model accuracy decreases
Solution Approach 1:
The patent addresses the non-uniform distribution problem by transforming the data from a simple path-based one-dimensional collection into a two-dimensional spatial distribution through position correction. By correcting positions to account for time lag, the system effectively redistributes fingerprints across the spatial domain, creating a more uniform coverage that improves model training without complicating the collection process
Data Source
AI summary
Provided is a computer-implemented method including acquiring a first pieces of observation data that include a position of a mobile object and a received signal strength of a wireless signal observed by the mobile object; and correcting each position of the mobile object included in each piece of observation data of the first pieces of observation data using one position of the mobile object at a time before the received signal strength included in the piece of observation data is observed.