GNSS Error Quantification for Local Map Global Alignment
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Solution Overview
Problem
Current GNSS systems and map alignment methods fail to account for GNSS errors introduced by regional environmental variations such as geographical features or tall structures, leading to inaccuracies in vehicle navigation and mapping.
Innovation Solution
A method and system for quantifying GNSS errors at multiple locations using simultaneous localization and mapping (SLAM) to identify anchor points, aligning local maps with a global coordinate system through a two-stage alignment process involving different subsets of anchor points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional GNSS systems are used for vehicle navigation, then the system is simple and easy to operate, but the positioning accuracy deteriorates due to environmental variations such as geographical features or tall structures
Solution Approach 1:
The patent introduces local maps as an intermediary between GNSS and the final position determination. These maps contain pre-collected observation data from multiple locations, which serve as reference information to correct GNSS errors caused by environmental factors like tall structures and geographical features
Solution Approach 2:
The system implements feedback by comparing real-time GNSS positions with historical observation data from local maps. The position estimation module uses this feedback to identify and correct systematic errors, continuously improving positioning accuracy in challenging environments
2Measurement precision
If local maps are collected from multiple vehicles using SLAM to quantify GNSS errors, then the positioning accuracy improves, but the data collection and processing complexity increases
Solution Approach 1:
The local maps serve multiple functions: they store historical observation data for error quantification, provide reference information for position estimation, and enable error correction across different vehicles and locations. This multi-functionality justifies the complexity by providing comprehensive benefits
Solution Approach 2:
The system performs preliminary actions by pre-collecting and storing observation data from multiple vehicles using SLAM before actual navigation. This pre-processing creates a library of reference data that simplifies real-time error quantification and correction operations
3Measurement precision
If a two-stage alignment process is used to align local maps with the global coordinate system, then the alignment accuracy improves, but the computational time and complexity increase
Solution Approach 1:
The alignment process is segmented into two distinct stages: first aligning local maps with initial GNSS positions to establish a baseline, then refining the alignment using quantified GNSS errors and anchor points. This segmentation allows each stage to focus on specific aspects of alignment, improving overall accuracy while managing computational complexity
Data Source
AI summary
A method for aligning a plurality of local maps with a global coordinate system includes quantifying a global navigation satellite system (GNSS) error at each of a plurality of locations within an environment. The method further includes determining a plurality of anchor points within the environment based at least in part on the GNSS error at each of the plurality of locations. The method further includes aligning the plurality of local maps with the global coordinate system based at least in part on the plurality of anchor points.