Vehicle Positioning via Server-Mediated GNSS Correction Data
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Solution Overview
Problem
Current navigation systems face challenges in achieving high positioning accuracy due to factors like satellite geometry, signal blockage, and atmospheric conditions, which are particularly problematic for applications such as autonomous driving that require greater precision.
Innovation Solution
The solution involves using a network of vehicles to share and process correction data, where a reference station generates and shares offset parameters or raw GNSS data to enable differential algorithms, allowing vehicles to improve their positioning accuracy even when out of signal range by extending the reference station's range through data sharing and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a reference station shares correction data directly, then positioning accuracy is improved for vehicles within signal range, but vehicles outside signal range cannot benefit from the correction data
Solution Approach 1:
A server acts as an intermediary between the reference station and vehicles. The server receives correction data from the reference station, stores it, and distributes it to vehicles that are outside the direct signal range of the reference station. This mediator enables correction data to reach vehicles beyond the original signal applicability range while maintaining positioning accuracy improvements.
Solution Approach 2:
The system transitions from direct one-to-one communication between reference station and vehicles to a many-to-many communication model through the server. Correction data is transmitted in a different dimension (through the network infrastructure) rather than through direct radio signal propagation, allowing vehicles outside the original signal range to access the correction data.
2Adaptability or versatility
If correction data is shared across a network, then coverage range is extended, but data transmission and processing complexity increases
Solution Approach 1:
The server performs multiple functions: receiving correction data from the reference station, storing the correction data, managing data distribution to multiple vehicles, and handling communication protocols. This multi-functional approach consolidates complexity into a single device rather than requiring each vehicle to independently manage correction data reception and distribution.
Solution Approach 2:
Vehicles autonomously determine their positioning needs and request correction data from the server when they are outside direct reference station range. The system enables vehicles to self-manage their positioning accuracy requirements without requiring complex centralized control for each individual positioning request.
3Measurement precision
If vehicles process raw GNSS data locally, then positioning accuracy is improved, but computational requirements and energy consumption increase
Solution Approach 1:
The reference station performs preliminary processing of raw GNSS data to generate correction data before distribution. This pre-processing eliminates the need for each vehicle to perform computationally intensive differential algorithms locally, reducing energy consumption while maintaining positioning accuracy improvements through the use of pre-computed correction parameters.
Data Source
AI summary
Various vehicle technologies for improving positioning accuracy despite various factors that affect signals from navigation satellites. Such positioning accuracy is increased via determining an offset and communicating the offset in various ways or via sharing of raw positioning data between a plurality of devices, where at least one knows its location sufficiently accurately, for use in differential algorithms.