Hybrid GNSS and Street Level Station Ranging Positioning
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Solution Overview
Problem
Current GNSS technologies face challenges in achieving high positioning accuracy, especially in urban environments due to satellite geometry, signal errors, and multipath effects, while vision-based SLAM methods are computationally complex and lack global positioning accuracy in low visibility scenarios.
Innovation Solution
A system and method that combines GNSS with ranging technologies like wireless RF, Visible Light Communication, and Lidar, using a network of street-level stations and a ranging server to enhance positioning accuracy by conducting ranging measurements and calculating user device positions based on the global positions of these stations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GNSS technology is used for positioning, then global position can be obtained, but positioning accuracy deteriorates in urban environments due to satellite geometry, signal errors, and multipath effects
Solution Approach 1:
The patent combines GNSS satellite-based ranging with terrestrial Street Level Station (SLS)-based ranging to create a hybrid positioning system. The user device performs both GNSS measurements and SLS ranging measurements, then fuses these measurements to compute position. This merging compensates for GNSS weaknesses in urban environments by adding a terrestrial reference system that is not affected by satellite geometry or multipath effects from satellites.
Solution Approach 2:
Street Level Stations act as intermediary reference points between the user device and the global positioning system. Instead of relying solely on distant satellites, the system introduces local SLS intermediaries that provide stable, ground-based ranging references. These intermediaries mitigate the harmful effects of urban canyons and multipath propagation by providing direct line-of-sight or controlled propagation paths for ranging signals.
2Measurement precision
If vision-based SLAM is used for positioning, then localization solution can be obtained, but computational complexity increases significantly due to image processing requirements
Solution Approach 1:
The patent replaces complex vision-based image processing with simpler radio-frequency or optical ranging measurements. Instead of capturing and processing images to extract feature points and compute relative position, the system uses time-of-flight or phase-based ranging signals to directly measure distance to SLSs. This substitution dramatically reduces computational complexity while maintaining or improving positioning accuracy.
Solution Approach 2:
The system changes the measurement parameter from image data (complex, high-dimensional) to ranging measurements (simple, scalar distance values). By transitioning from visual feature matching to direct distance measurement via signal time-of-flight or phase difference, the computational burden is reduced from complex image processing algorithms to straightforward distance calculation and trilateration.
3Measurement precision
If vision-based SLAM is used for positioning, then relative localization can be obtained, but global position accuracy deteriorates in low visibility scenarios
Solution Approach 1:
The patent creates a positioning system that serves multiple environments and conditions through the SLS-based ranging approach. The same SLS infrastructure and ranging methodology work effectively whether visibility is high or low, whether in urban canyons or open spaces, and whether complementing GNSS or operating independently. This universal approach eliminates the visibility-dependent limitations of vision-based SLAM.
Data Source
AI summary
A system and method for positioning based on navigation systems. The method includes receiving a list of Street Level Stations (SLSs), conducting ranging measurements with each SLS identified within the received list, receiving a global position of the each SLS identified within the received list, and computing a position of a user device based on the ranging measurements and a position of the each SLS identified within the received list.


