Ionosphere Model Accuracy Generation for GNSS Positioning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for improving GNSS positioning accuracy, such as precise point positioning, are limited by long convergence times due to reliance on inaccurate ionosphere models, which are not reflective of inhomogeneities and do not provide direct true error references.
Innovation Solution
A method that utilizes phase observations with fixed or converged ambiguities to generate accuracy information for ionosphere models, accounting for inhomogeneities through vertical residual analysis and scale factor computation, providing quasi-true error representations for improved model accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional ionosphere models are used for GNSS positioning, then the model structure is simple and easy to implement, but the positioning accuracy is limited to meter-level due to inhomogeneities and lack of true error references
Solution Approach 1:
The patent applies local quality by generating accuracy information specifically for regions with sufficient pierce points (where number of pierce points exceeds threshold number). The accuracy indicator is computed locally at each grid point based on vertical residual information from nearby pierce points, allowing the model to provide centimeter-level accuracy where data is available while maintaining simplicity in regions with insufficient data.
Solution Approach 2:
The patent performs preliminary action by pre-computing accuracy information for the ionosphere model before actual positioning operations. The processing entity calculates vertical residual information, identifies pierce points within threshold distances, and generates accuracy indicators in advance, so that receivers can directly use this pre-computed information to achieve faster convergence and higher accuracy without performing complex calculations in real-time.
2Measurement precision
If precise point positioning methods are used to improve positioning accuracy, then centimeter-level accuracy can be achieved, but the convergence time is excessively long due to reliance on inaccurate ionosphere models
Solution Approach 1:
The patent implements feedback by using fixed or converged ambiguities from phase observations to generate vertical residual information, which then feeds back into computing the accuracy indicator. This feedback loop allows the system to continuously refine the accuracy information based on actual observation residuals, enabling receivers to quickly assess model accuracy and converge to centimeter-level positioning without excessively long convergence times.
Solution Approach 2:
The processing entity performs preliminary computation of accuracy information including vertical residual information and accuracy indicators before the receiver performs positioning. This pre-computation of accuracy metrics allows the receiver to immediately utilize accurate ionosphere model information, significantly reducing the time required for the positioning solution to converge from float to fixed ambiguities.
3Measurement precision
If phase observations with fixed ambiguities are used to generate accuracy information, then the accuracy indicator reflects true error references, but the processing complexity and computational requirements increase
Solution Approach 1:
The patent applies segmentation by dividing the accuracy computation into distinct modular steps: (1) obtaining vertical residual information from phase observations with fixed ambiguities, (2) computing pierce point coordinates using ionosphere single layer model, (3) identifying pierce points within threshold distances at each grid point, (4) computing accuracy indicators based on vertical residuals. This segmentation allows each step to be processed independently and efficiently, managing complexity while maintaining high accuracy.
Solution Approach 2:
The patent introduces an intermediary processing entity that acts as a mediator between the complex accuracy computation and the simple receiver implementation. The processing entity performs the computationally intensive tasks of obtaining vertical residuals, computing pierce points, identifying nearby pierce points, and generating accuracy indicators, then provides the simplified accuracy information to receivers. This intermediary approach maintains high accuracy while reducing receiver processing complexity.
4Reliability
If the ionosphere model accounts for inhomogeneities through vertical residual analysis, then the accuracy information becomes more reliable, but the number of computations and data requirements increase
Solution Approach 1:
The patent applies local quality by computing accuracy information only at grid points where the number of pierce points exceeds a threshold number. This selective approach ensures reliability is improved only where sufficient data exists, while avoiding unnecessary computations in regions with insufficient observations. The vertical residual analysis is performed locally at each grid point using only the pierce points within threshold distance, optimizing the balance between reliability and data requirements.
Data Source
Figure 1
Figure 2
Figure 3~4
AI summary
The present invention relates to a method for generating accuracy information for an ionosphere model. For each of at least some of the phase observations having fixed or converged ambiguities, phase residual information of a parameter estimation procedure is obtained and coordinates of a pierce point on a sphere around the earth are computed. The sphere is defined by an ionosphere single layer model. The coordinates indicate where the path of the signals from which the phase observation has been obtained pierces the sphere. Then the phase residual information of the corresponding phase observation is mapped, for each pierce point, to the vertical at the pierce point to generate vertical residual information, Furthermore a grid of equidistant points (grid points) is put on the sphere and, for each of at least some of the grid points, pierce points are identified within a threshold distance from the grid point on the sphere. Then grid points are selected for which the number of identified pierce points exceeds a threshold number. For each selected grid point, vertical accuracy information is computed at the selected grid point based on the vertical residual information of the identified pierce points, and a scale factor is computed based on the vertical accuracy residual information computed for the selected grid point. Finally, the accuracy information for the ionosphere model is generated based on the vertical accuracy information computed for the selected grid points and an overall scale factor computed based on the computed scale factors.