Ionosphere Modeling for GNSS Ambiguity Resolution
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Solution Overview
Problem
Current ionospheric modeling and ambiguity resolution techniques in Global Navigation Satellite Systems (GNSS) are inefficient, leading to errors in position fixing due to lumping residual errors together without considering individual characteristics like short-range correlations in multipath and long-range correlations in the ionosphere, and fail to provide detailed corrections across local networks.
Innovation Solution
The proposed solution employs a computationally efficient method that models the ionosphere in terms of 'total electron content' and treats ionospheric effects directly in terms of phase advance, using geometry-free Kalman filters to estimate ionospheric parameters and carrier-phase ambiguities, allowing for better error estimation and faster ambiguity resolution across networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional network techniques are used to calculate pseudorange corrections by interpolating residual errors of reference stations, then position estimation can be obtained, but errors are lumped together without considering individual characteristics like short-range correlations in multipath and long-range correlations in the ionosphere, leading to reduced accuracy
Solution Approach 1:
The patent segments the total error into distinct components: multipath errors and ionospheric errors. Each component is modeled and corrected separately using appropriate techniques (multipath correction for short-range correlations and ionospheric modeling for long-range correlations), rather than treating all errors as a single residual to be interpolated.
Solution Approach 2:
The patent introduces an intermediary error model that acts as a mediator between raw measurements and final position estimates. This model explicitly accounts for the statistical characteristics and correlations of different error sources, allowing for more accurate separation and correction of individual error components before position calculation.
2Measurement precision
If carrier-phase measurements are used to achieve millimeter to centimeter accuracy, then relative position can be estimated with high precision, but accurate phase measurement requires good knowledge of ionospheric effects for all observation times, increasing system complexity
Solution Approach 1:
The patent applies preliminary ionospheric correction using a dedicated ionospheric model before performing carrier-phase ambiguity resolution. By pre-characterizing the ionospheric effects based on total electron content and signal geometry, the system prepares corrected measurements in advance, simplifying the subsequent high-precision positioning calculations.
Solution Approach 2:
The patent changes the parameter representation of ionospheric effects from complex spatio-temporal variations to a more manageable form based on total electron content (TEC) and signal geometry. This parameter transformation simplifies the ionospheric modeling requirements while maintaining the accuracy needed for carrier-phase measurements.
3Measurement precision
If multiple reference stations are deployed to provide correction terms across a network, then position accuracy can be improved through interpolation, but the number of parameters to be estimated increases, reducing computational efficiency
Solution Approach 1:
The patent extracts and removes the dominant ionospheric error component through dedicated ionospheric modeling based on TEC. By taking out this systematic error source before network processing, the remaining errors are smaller and require fewer correction parameters, reducing the computational burden while maintaining accuracy benefits from multiple reference stations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach improves position-fixing performance and reliability, enables faster correction provision to rovers, and provides insight into ionospheric dynamics, even for single-frequency receivers, by exploiting correlations within the ionosphere and reducing the number of parameters to be estimated.
Implementation Method 1
When the signals radiated from the satellites penetrate this medium on their way to the ground-based receivers, they experience delays in their signal travel times and shifts in their carrier phase (phase advance)
Data Source
AI summary
Methods and apparatus which characterize the ionospheric error across a network of GNSS reference stations are presented. The method relies on dual-frequency phase measurements in a geometry-free linear combination. The data are filtered for ambiguities and the characteristic parameters of the ionosphere. In combination with filter results from other combinations of phase measurements (ionosphere free combination), the physically-based model provides rapid and reliable ambiguity resolution.