Validating Map Data for UE Positioning Accuracy
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Solution Overview
Problem
Current positioning methods in 5G wireless communication systems face challenges in accurately determining the position and direction of user equipment (UE) due to inconsistencies between positioning information, motion data, and map data, especially in environments with multipath reception and high dynamic movement, leading to inaccurate position estimates and unreliable navigation.
Innovation Solution
The implementation of a UE that includes a processor to validate the consistency of positioning information, motion data, and map data, using sensors like accelerometers, magnetometers, and gyroscopes to determine a validity status, and then using valid map data to constrain position estimates and disregard outlier measurements, thereby improving positioning accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If positioning information from multiple sources is used to determine UE position and direction, then positioning coverage and signal availability are improved, but measurement consistency and positioning accuracy deteriorate due to multipath reception and high dynamic movement
Solution Approach 1:
The system validates map data by comparing predicted UE positions and directions (derived from positioning information and motion data) against actual map features, generating a validity status that feeds back into the positioning process. This feedback mechanism filters inconsistent measurements and maintains positioning accuracy despite using multiple positioning sources in challenging environments.
Solution Approach 2:
Map data serves as an intermediary validation layer between raw positioning measurements and final position estimates. The system uses map features as intermediate reference points to verify whether predicted UE positions are physically plausible, thereby resolving inconsistencies from multipath reception and high dynamic movement before final positioning output.
2Measurement precision
If map data is used to constrain position estimates and filter outlier measurements, then positioning accuracy is improved, but system complexity increases due to additional validation processing
Solution Approach 1:
The system performs preliminary validation of map data consistency before using it to constrain position estimates. By pre-validating map data against positioning information and motion data to generate a validity status, the system avoids complex real-time filtering during positioning calculations, reducing processing complexity while maintaining accuracy improvements.
3Reliability
If validity status of map data is determined based on consistency between positioning information, motion data, and map data, then reliability of positioning output is improved, but computational load increases
Solution Approach 1:
The system applies partial validation by determining validity status based on key consistency checks between positioning information, motion data, and map data features rather than exhaustive verification of all parameters. This selective validation approach maintains positioning reliability while reducing computational energy consumption compared to complete consistency verification.
Data Source
AI summary
A method being for facilitating positioning determination of a UE includes: obtaining motion information indicative of motion of the UE; obtaining positioning information based on positioning signals received by the UE; determining a validity status of map data based on whether the positioning information, the motion of the UE, and the map data, that include locations of physical environmental features, are consistent, wherein the validity status is determined to be valid in response to the positioning information, the motion of the UE, and the map data being consistent; and determining at least one of a position estimate for the UE, or a direction of motion of the UE, based on the map data and based on the validity status being valid.