GNSS Rover Positioning with Known Position Aiding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current Global Navigation Satellite Systems (GNSS) processing techniques face challenges in achieving rapid and efficient convergence to high precision positioning, particularly due to satellite tracking interruptions and limitations in data processing power of rover processors, which hinder the achievement of cm-level accuracy and availability.
Innovation Solution
The proposed solution employs a combination of tropospheric and ionospheric bridging techniques, along with known position aiding, using the Factorized Multi-Carrier Ambiguity (FAMCAR) algorithm and distributed filtering to estimate carrier phase ambiguities and rover antenna position, enabling rapid re-convergence and improved accuracy by predicting biases and leveraging known rover positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional GNSS processing techniques are used, then positioning accuracy can eventually reach cm-level, but convergence time is excessively long (10-30 minutes)
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing ionospheric delay models and atmospheric correction parameters before actual positioning is needed. When a tracking interruption occurs, these pre-prepared correction data can be immediately applied without requiring lengthy re-convergence, thus resolving the contradiction between achieving high precision and minimizing convergence time
Solution Approach 2:
The patent changes key processing parameters by introducing aided ionospheric delay parameters and using multi-frequency carrier phase measurements with different weighting schemes. By dynamically adjusting these parameters based on signal quality and convergence state, the system can achieve cm-level accuracy much faster than traditional methods while handling tracking interruptions efficiently
2Measurement precision
If rover processor computes all parameters independently, then positioning accuracy can be maintained, but processing complexity and computational burden increase
Solution Approach 1:
The patent segments the complex positioning computation into distinct modules: one for computing geometric ranges and basic positioning, another for calculating ionospheric delay corrections, and a third for integrating multi-frequency carrier phase measurements. This segmentation allows each module to be optimized independently and processed in parallel, reducing overall computational burden while maintaining cm-level accuracy
Solution Approach 2:
The patent introduces an intermediary computation layer that processes atmospheric correction parameters and ionospheric delay models separately from the main positioning calculation. This intermediary layer pre-processes correction data that can then be efficiently applied to multiple positioning solutions, reducing the computational complexity at the rover processor while preserving accuracy
3Reliability
If tracking interruptions occur, then system availability is reduced, but re-convergence time determines actual operational availability
Solution Approach 1:
The patent implements beforehand cushioning by maintaining buffered correction data and备用 (backup) ionospheric delay models that can be immediately deployed when tracking interruptions occur. This pre-prepared cushion of correction data ensures that re-convergence can begin instantly without waiting for new satellite passes or correction data, thereby maintaining system availability despite interruptions
Solution Approach 2:
The patent employs feedback mechanisms that continuously monitor tracking quality and convergence status. When a tracking interruption is detected, the feedback loop triggers immediate re-initialization using pre-stored correction parameters and adjusts processing weights to accelerate re-convergence. This closed-loop feedback ensures rapid recovery and minimizes the impact of interruptions on overall system availability
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Methods and apparatus provide for positioning of a rover antenna from GNSS data derived from multi-frequency signals and correction data derived from a network of reference stations. At each of a plurality of epochs, the GNSS data and correction data are used to estimate values defining a rover antenna position and a set of multi- frequency ambiguities. An ionospheric- free carrier-phase ambiguity per satellite is estimated based on a known rover antenna position. The estimated ionospheric-free carrier-phase ambiguity is combined with an estimated widelane ambiguity and with an estimated ionospheric-free ambiguity and with values defining the known rover antenna position to obtain values defining an aided rover antenna position and aided multi-frequency ambiguities.