Offline Radio Map Tile Segmentation for GNSS Rescue
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Solution Overview
Problem
Existing offline radio map solutions for mobile devices are excessively large in size, leading to increased consumption of bandwidth, energy, and storage resources, as they include unnecessary data for areas where GNSS positioning works, and fail to optimize data representation for areas with low demand for high-quality positioning.
Innovation Solution
A mobile device identifies device-specific GNSS rescue areas where GNSS is unreliable and downloads a partial radio map only for these areas, optimizing the offline radio map to reduce unnecessary data and enhance resource efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a complete radio map is downloaded for offline positioning, then positioning availability is improved, but data size and resource consumption increase excessively
Solution Approach 1:
The radio map is segmented into multiple tiles organized in a hierarchical structure. Instead of downloading a complete radio map, only the necessary tiles covering the user's current location and surrounding areas are downloaded. This segmentation allows the system to provide offline positioning for specific regions while keeping the downloaded data size manageable.
Solution Approach 2:
The system implements adaptive tile download strategies that prioritize areas with higher positioning demands or poorer GNSS coverage. Tiles are selectively downloaded based on user behavior patterns, historical positioning needs, and predicted future locations. This ensures that offline positioning capability is optimized for locally important areas while minimizing overall data consumption.
2Quantity of substance
If radio map data is compressed to reduce size, then storage and bandwidth consumption decrease, but positioning accuracy may deteriorate
Solution Approach 1:
The system employs lossless compression algorithms specifically optimized for radio map data structures. By changing the data representation parameters and using efficient encoding schemes, the system achieves significant compression ratios while preserving all positioning-relevant information intact, thus maintaining positioning accuracy.
3Ease of operation
If a pre-defined radius area is used for offline radio map download, then download simplicity is improved, but unnecessary data is included for areas with low positioning demand
Solution Approach 1:
The system dynamically adjusts the download area and scope based on real-time factors including user movement patterns, predicted destination, current location accuracy, and historical positioning behavior. Instead of using a static pre-defined radius, the download boundary adapts to user needs, ensuring that offline radio map data is downloaded for areas where the user is likely to need positioning while avoiding unnecessary downloads for low-demand areas.
Data Source
AI summary
In accordance with the disclosed approach, positioning server(s) could receive, from mobile devices, information indicating a plurality of GNSS rescue areas, each respective GNSS rescue area of the plurality of GNSS rescue areas corresponding to a respective geographic area visited by a respective one of the mobile devices in which (i) at least one GNSS-based position estimate is or was unavailable and (ii) the respective mobile device had demand for positioning data of at least a particular quality level. Given this, the server(s) could generate a GNSS rescue map representing radio data for the plurality of GNSS rescue areas. In this way, the server(s) could transmit, to a mobile device, an offline radio map representing a subset of the GNSS rescue map, to provide radio data for at least one of the GNSS rescue areas or portion thereof.