Synthesized Base Station Data for GNSS Positioning Accuracy
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Solution Overview
Problem
Current GNSS signal processing methods face challenges in accurately determining the position of a rover antenna due to limitations in obtaining precise satellite data and efficiently generating and applying differential processes for real-time kinematic processing.
Innovation Solution
The method involves obtaining rover GNSS data from code and carrier phase observations, determining a virtual base station location, generating synthesized base station data, and applying differential processing techniques such as real-time kinematic (RTK) or instant real-time kinematic (IRTK) processing to determine the rover antenna's position, using a network processor architecture that includes standard clock, Melbourne-Wübbena bias, orbit, and phase clock processors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional GNSS signal processing methods are used, then the system structure is simple, but the positioning accuracy and speed are insufficient
Solution Approach 1:
The system segments the base station functionality by creating a virtual base station through software synthesis rather than requiring multiple physical base stations. The base station data is divided into synthesized components that can be generated computationally from satellite data and virtual location information, reducing hardware complexity while maintaining positioning accuracy.
Solution Approach 2:
A virtual base station acts as an intermediary between satellite data and rover positioning. Instead of directly processing satellite signals at multiple physical locations, the system uses a virtual base station to synthesize reference data that mediates the positioning calculation, improving accuracy without proportionally increasing system complexity.
2Measurement precision
If real-time kinematic processing is applied, then positioning accuracy improves, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary actions by pre-generating synthesized base station data for multiple epochs before actual positioning calculations. Virtual base station locations are determined in advance, and reference data is synthesized ahead of time, allowing faster real-time processing without sacrificing the accuracy benefits of RTK processing.
Solution Approach 2:
The system dynamically adjusts the virtual base station location based on rover position updates. As the rover moves, the virtual base station location is updated accordingly, allowing the system to maintain optimal positioning accuracy while adapting to changing conditions without requiring complete reprocessing.
3Measurement precision
If multiple epochs of precise satellite data are processed, then positioning accuracy improves, but data processing complexity and time increase
Solution Approach 1:
The system creates copies of base station data through synthesis rather than requiring multiple physical base stations. Synthesized base station data is generated as computational copies that replicate the functionality of physical reference stations, enabling multi-epoch processing with reduced complexity by using software-generated data instead of additional hardware.
Data Source
AI summary
Methods and apparatus are described for determining position of a rover antenna, comprising: obtaining rover GNSS data derived from code observations and carrier phase observations of GNSS signals of multiple satellites over multiple epochs, obtaining precise satellite data for the satellites, determining a virtual base station location, generating epochs of synthesized base station data using at least the precise satellite data and the virtual base station location, and applying a differential process to at least the rover GNSS data and the synthesized base station data to determine at least rover antenna positions.