Map-Filtered Positioning Using GNSS and Sensor Trajectories
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Solution Overview
Problem
Existing wireless communication systems, particularly in the context of 5G, face challenges in providing highly accurate positioning for autonomous driving applications due to environmental factors and multipath interference, which can affect the reliability of vehicle-to-everything (V2X) communication technologies.
Innovation Solution
A method and apparatus that utilize global navigation satellite system (GNSS) positions and sensor-based trajectories to filter map data, determining a position estimate for a user device by refining possible routes based on specific criteria, thereby enhancing positioning accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If map data is used for positioning in 5G wireless communication systems, then positioning capability is provided, but positioning accuracy deteriorates due to environmental factors and multipath interference
Solution Approach 1:
The system performs preliminary filtering of map data by comparing it with sensor-based trajectory data before using it for positioning. This advance verification step removes unreliable map data that could cause positioning errors, thereby maintaining positioning capability while improving accuracy.
Solution Approach 2:
The system uses sensor-based trajectory information as feedback to validate and refine map data. By continuously comparing map data against actual sensor measurements, the system corrects positioning errors caused by environmental factors and multipath interference, improving overall positioning accuracy.
2Measurement precision
If map data filtering is performed to improve positioning accuracy, then positioning precision is improved, but processing complexity increases
Solution Approach 1:
The system extracts and separates the filtering function from the main positioning processing. By taking out the map data filtering step and handling it through comparison with sensor trajectory data, the system reduces the complexity burden on the main positioning algorithm while still achieving improved precision.
Solution Approach 2:
The positioning process is segmented into distinct stages: map data acquisition, sensor trajectory generation, filtering/comparison stage, and final positioning calculation. This segmentation allows each stage to be optimized independently, reducing overall processing complexity while maintaining high positioning precision.
Data Source
AI summary
In an aspect, a user device or a server may obtain a global navigation satellite system (GNSS) position of the user device, a sensor-based trajectory of the user device, or both. The user device or the server may filter map data indicating possible routes of the user device based on one or more criteria associated with the GNSS position, the sensor-based trajectory, or both to obtain filtered map data. The user device or the server may determine a position estimate for the user device based on the filtered map data.


