Radio Map Quality via Feedback Loop Exclusion
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Solution Overview
Problem
Existing positioning technologies face challenges in accurately modeling radio environments due to unsuitable data from mobile radio nodes, leading to inaccurate position estimates, especially in scenarios where radio nodes move, and current methods for identifying such nodes are computationally intensive and prone to errors.
Innovation Solution
A feedback loop is established between a radio-based positioning system and a client, such as a tracking system, to identify and exclude radio nodes associated with incorrect position estimates by using a location trace to determine outliers, thereby improving the quality of radio maps and position estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If machine learning techniques are applied to determine which radio nodes are mobile, then identification accuracy may improve, but computational complexity and processing time increase significantly
Solution Approach 1:
The patent implements a feedback mechanism where position estimates are continuously monitored and compared against expected values based on location traces. When deviations indicate mobile radio nodes, the system automatically identifies and excludes these nodes from radio map generation. This feedback-based approach replaces complex machine learning with a simpler iterative process that achieves accurate identification without high computational complexity.
Solution Approach 2:
The system uses its own position estimation outputs and location trace data to automatically identify mobile radio nodes. By leveraging internally generated data (position estimates, location traces) rather than requiring external machine learning models, the system performs self-diagnosis and self-correction, eliminating the need for computationally intensive external algorithms.
2Measurement precision
If machine learning techniques are applied to identify mobile radio nodes, then identification capability improves, but error rates increase due to data availability constraints
Solution Approach 1:
The continuous feedback loop monitors position estimates against location traces and adjusts identification of mobile nodes in real-time. This iterative refinement allows the system to adapt to varying data conditions and reduce errors that would occur with static machine learning models trained on insufficient data.
Solution Approach 2:
The system pre-establishes location traces and expected position patterns before needing to identify mobile nodes. These preliminary data structures enable more reliable identification by providing a baseline for comparison, reducing errors when actual position estimates are evaluated against pre-computed expectations.
3Adaptability or versatility
If comprehensive crowdsourced data is collected for radio map generation, then positioning coverage improves, but accuracy degrades due to inclusion of mobile radio node data
Solution Approach 1:
The patent extracts and removes data from mobile radio nodes from the crowdsourced dataset. By identifying nodes whose positions deviate from expected location traces and excluding their measurements from radio map generation, the system maintains comprehensive coverage from stationary nodes while eliminating accuracy-degrading mobile node data.
Solution Approach 2:
The system uses feedback from position estimation accuracy to identify and exclude mobile radio node data. By continuously monitoring whether position estimates match expected values and excluding data from nodes that cause deviations, the system maintains high accuracy while preserving comprehensive coverage from valid stationary nodes.
Data Source
AI summary
Disclosed is an approach for improving positioning quality via a feedback loop between a radio-based positioning system and a client device, such as a tracking system. In particular, the tracking system or other client device may request and then receive a position estimate from the positioning system. The tracking system could then make a determination that the position estimate is incorrect, such as by determining that it is an outlier relative to a location trace, for instance. Responsive to this determination, the tracking system may transmit, to the position system, an indication of radio node(s) associated with the incorrect position estimate. Based on this indication, the positioning system could then exclude one or more of those radio node(s) from a radio map, thereby improving quality of the radio map and in turn quality of future position estimates, among other advantages.