Ionosphere Spatial Interpolation for Fast PPP-RTK Convergence
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Solution Overview
Problem
Existing Global Navigation Satellite Systems (GNSS) face challenges in achieving fast and high-accuracy position determination due to excessive convergence times in precise point positioning (PPP) methods, particularly in sparse regional networks and during active ionospheric disturbances.
Innovation Solution
Implementing a method for precise point positioning that includes generating predicted Slant Total Electron Content (STEC) estimations, detecting and filtering out outliers, and using dynamic interpolation algorithms to enhance ionospheric modeling, incorporating a STEC processor to handle sparse network coverage and real-time ionospheric variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If precise point positioning (PPP) methods are used to increase position determination accuracy, then positioning accuracy is improved, but convergence time becomes excessive
Solution Approach 1:
The system pre-calculates and stores ionospheric delay corrections at a network center using data from multiple reference receivers. These pre-computed corrections are then rapidly distributed to user receivers, eliminating the need for users to perform lengthy self-calibration and enabling fast convergence to high-accuracy positioning
Solution Approach 2:
A network center acts as an intermediary between reference receivers and user receivers. The network center collects STEC measurements from multiple references, computes corrected ionospheric parameters, and provides these corrections to users. This intermediary process enables rapid convergence without requiring users to perform complex self-calibration
2Area of stationary object
If spatial interpolation is used in sparse regional networks, then positioning service coverage is extended, but interpolation quality deteriorates during active ionospheric disturbances
Solution Approach 1:
The system continuously monitors ionospheric activity using STEC measurements from multiple reference receivers and adjusts interpolation parameters in real-time. During active ionospheric disturbances, the system detects increased variability and adapts the interpolation algorithm to account for these conditions, maintaining interpolation quality even in sparse networks
Solution Approach 2:
The system dynamically changes interpolation parameters based on ionospheric activity levels. During stable conditions, standard interpolation is used, but during active disturbances, the system adjusts parameters such as smoothing coefficients and weighting factors to maintain interpolation accuracy despite increased ionospheric variability
3Reliability
If outlier detection and filtering are applied to STEC estimations, then reliability of positioning is improved, but processing complexity increases
Solution Approach 1:
The system replaces complex manual or heuristic outlier detection methods with automated statistical tests based on a posteriori residuals. The differenced STEC spatial approximation generates residual values that are automatically compared against thresholds, providing reliable outlier detection through systematic mathematical criteria rather than ad hoc methods
Data Source
AI summary
A method and system for high-quality ionosphere spatial interpolation is designed to improve outlier detection and accuracy estimation in regional networks to accelerate convergence of PPP-RTK positioning services. STEC estimations from a regional receiver network undergo a sequence of anomaly detection steps including jump detection by Alpha-Beta filtering, outlier detection by a posteriori residuals from differenced STEC spatial approximation and by cross-validation of differenced STEC values. The method further includes generating an estimation of ionosphere activity indicator which is further used in outlier detection. On-the-fly estimation of the indicator provides more robust STEC outliers detection because it accounts for systematic periodic changes in ionosphere activity and for spatial correlation of the ionosphere.