Dual Error Model for Long-Baseline RTK Scintillation Compensation
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Solution Overview
Problem
Long-baseline RTK configurations are vulnerable to ionospheric variations, leading to satellite signal diffraction, phase shifts, and amplitude fades, which result in position bias and loss of signal quality.
Innovation Solution
A system and method that utilize a rover receiver in wireless communication with a base station receiver to obtain initial code pseudo-range and carrier phase measurements, with the base station generating measurement range errors and atmospheric-related aiding data, which are then used by the rover to correct measurements and mitigate errors using a dual error model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If long-baseline RTK is used to extend positioning range, then coverage area is increased, but positioning accuracy deteriorates due to ionospheric variations
Solution Approach 1:
The patent introduces a dual error model as an intermediary mechanism that mediates between the base station corrections and the rover positioning calculation. This model separately estimates ionospheric delay errors and multipath errors, allowing the system to compensate for ionospheric variations that normally degrade long-baseline RTK accuracy, thereby maintaining positioning accuracy across extended coverage areas.
Solution Approach 2:
The patent changes the error modeling parameters by transitioning from a single error model to a dual error model that independently parameters ionospheric delay and multipath effects. By estimating these errors separately with different statistical characteristics, the system can adaptively compensate for ionospheric variations, enabling accurate positioning over long baselines where traditional single-model approaches fail.
2Device complexity
If conventional error model is used, then system complexity is low, but reliability deteriorates under strong ionospheric activity
Solution Approach 1:
The patent segments the error modeling process into two independent components: ionospheric delay error estimation and multipath error estimation. Each component has its own statistical model and correction mechanism. This segmentation allows the system to address different error sources with appropriate models, significantly improving reliability under ionospheric activity while keeping each individual model relatively simple.
Solution Approach 2:
The patent creates a composite error model that combines multiple error estimation techniques (ionospheric modeling, multipath modeling, dual-frequency observations) into a unified dual error model. This composite approach leverages the strengths of different modeling techniques to achieve high reliability under varying ionospheric conditions, while the modular structure maintains manageable system complexity.
3Measurement precision
If dual error model is applied, then positioning accuracy is improved, but computational load increases
Solution Approach 1:
The patent performs preliminary estimation of ionospheric delay errors and multipath errors separately before the final positioning calculation. By pre-estimating these error components and their statistical characteristics, the system reduces the computational burden during real-time positioning, as the dual error model parameters are prepared in advance rather than calculated iteratively during position solving.
Solution Approach 2:
The dual error model is implemented in a self-service manner where the system automatically estimates and corrects for ionospheric and multipath errors using its own observational data and statistical models. This self-contained approach eliminates the need for complex external correction services or iterative refinements, achieving high positioning accuracy with moderate computational load through efficient use of available measurements.
Data Source
AI summary
The system and method facilitates Real-Time-Kinematic (RTK) GNSS with long baseline between a rover receiver and a base station receiver, even in the presence of scintillation or ionospheric disturbances that spatially fluctuate. Residual atmospheric errors can be estimated by a dual error model in a filter to promote efficient fixing or resolution of carrier phase ambiguities.