Crowd-Sourced GNSS Environment Characterization for Positioning Accuracy
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Solution Overview
Problem
Local environment measurement issues, such as multipath signal propagation, unintentional interference, intentional jamming, and spoofing, can degrade positioning performance in wireless communication systems, leading to inaccurate position estimates.
Innovation Solution
A method and system for crowd-sourcing GNSS local environment positioning metrics from devices, which are then used to provide assistance data to devices to handle local environment issues, thereby improving positioning accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If devices perform GNSS positioning measurements in challenging local environments, then positioning data can be obtained, but measurement precision deteriorates due to multipath propagation, interference, jamming, and spoofing
Solution Approach 1:
The system performs preliminary characterization of local environment conditions before positioning measurements are taken. The location server collects and analyzes positioning metrics from multiple devices to pre-identify challenging areas (urban canyons, regions with multipath, jamming zones). This preliminary characterization allows the system to prepare appropriate assistance data and filtering strategies in advance, improving measurement precision by anticipating and compensating for environmental harmful factors before they degrade positioning accuracy
Solution Approach 2:
The system implements a feedback mechanism where positioning metrics and measurements are continuously collected from devices, analyzed by the location server, and used to generate updated assistance data. The server monitors positioning performance metrics (signal quality, number of visible satellites, positioning accuracy estimates) and feeds this information back to devices as assistance data. This closed-loop feedback enables continuous improvement of positioning precision by adapting to changing local environment conditions in real-time
2Loss of information
If the location server collects positioning metrics from multiple devices to characterize local environment, then understanding of positioning performance improves, but device complexity and network processing load increase
Solution Approach 1:
Individual devices perform self-service by autonomously measuring and reporting their own positioning metrics (signal quality, satellite visibility, positioning accuracy) to the location server. Each device characterizes its own local environment conditions without requiring complex centralized control. This self-service approach reduces network processing complexity while still gathering comprehensive positioning performance data across multiple devices, as each device independently contributes to the collective understanding of local environment characteristics
Solution Approach 2:
The system segments the positioning characterization task into individual device-level measurements rather than requiring a single complex centralized measurement system. Each device independently measures local positioning metrics in its specific location, and the location server aggregates these segmented measurements to build a comprehensive picture of positioning performance across different geographic areas. This segmentation reduces the complexity burden on any single device or network component while improving overall positioning performance understanding
Data Source
AI summary
A method, system and apparatus for wireless device (WD) global navigation satellite system (GNSS) local environment characterization are disclosed. According to one aspect, a method in a network node includes obtaining a capability of the WD to provide GNSS positioning metrics from the WD. The method also includes requesting the WD to provide GNSS positioning metrics with a location estimate, when a location estimate is available at the WD. The method also includes receiving from a plurality of WDs, local GNSS positioning metrics associated to the reported location estimate. The method further includes determining local GNSS positioning metrics applicable to the plurality of WDs. The method also includes transmitting a set of local GNSS positioning metrics to at least one WD.