Regional Minimum Residual Estimation for Wi-Fi Positioning
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Solution Overview
Problem
Conventional navigation systems relying on GPS or Radio-Frequency methods become inaccurate or unusable when GPS signals degrade or are unavailable, leading to a need for improved positioning methods in portable devices.
Innovation Solution
The use of Wi-Fi access points data, combined with MEMS devices and a Regional Minimum Residual Estimation Filter (RMREF) method, to determine user position by calculating signal strength measurements and minimizing position residuals across a two-dimensional search grid, allowing for accurate navigation even with obstructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS or Radio-Frequency based positioning methods are used, then positioning accuracy is improved, but system reliability deteriorates when GPS signals degrade or become unavailable
Solution Approach 1:
The patent introduces Wi-Fi access points as an intermediary positioning mechanism. When GPS signals are unavailable or degraded, the system uses Wi-Fi signal strength measurements from multiple access points to estimate user position, thereby maintaining system availability and reliability without sacrificing positioning accuracy
2Reliability
If conventional Wi-Fi based positioning is used, then system availability is improved, but measurement precision deteriorates due to signal obstructions and multipath effects
Solution Approach 1:
The patent implements a feedback mechanism through the RMREF algorithm that continuously monitors position residuals and adjusts the search grid accordingly. The system uses the difference between true range (from access point locations) and computed range (from signal strength) to iteratively refine position estimates, compensating for obstructions and multipath effects to maintain both availability and precision
3Measurement precision
If a comprehensive search grid is used to minimize position residuals, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent applies a dynamic search grid approach where the grid dimensions and resolution are adjusted based on the current positioning context. The RMREF algorithm adapts the search grid size according to signal strength variations and position residual patterns, allowing the system to achieve high measurement precision while reducing computational complexity by focusing the search only where needed rather than using a fixed comprehensive grid
Data Source
AI summary
A computer-implemented method and device for determining a user position, implemented in a user handheld computing device programmed to perform the method. The method includes solving for the position of a user based on ranges, which are computed by estimating power loss between a user and a number of Wi-Fi Access Points. Embodiments of the present invention includes a method that is designed to accommodate the non-linear nature of solving a position solution using power estimates. This method includes solving a two-dimensional solution grid of position residuals, or magnitudes of error between true and computed ranges, using signal strength measurements from multiple Wi-Fi access points in order to determine local minima of the position residuals indicating a user position. Standard approaches in the area such as a Least Squares Solution overly simplify the non-linear components resulting in poor performance.