PPP-AR ambiguity error fixed integrity risk modeling method and device
By employing deseparation methods and multidimensional feature extraction, combined with logistic regression and fault tree analysis models, accurate identification and risk allocation of ambiguity errors in PPP-AR systems are achieved, enhancing the system's integrity assurance capabilities and making it suitable for high-reliability positioning applications with multiple constellations and frequencies.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-09
- Publication Date
- 2026-04-03
AI Technical Summary
In existing PPP-AR integrity studies, the fixed probability of errors is difficult to quantify in real time, multi-source observation information is not fully explored, multi-source observation features are not jointly modeled, and the protection-level calculation is not coupled with the fixed probability of errors, resulting in a high misjudgment rate in complex environments and failing to meet the integrity risk indicators.
The deseparation method is used to determine whether the satellite ambiguity is correctly fixed epoch by epoch, generate fixed correctness labels and extract multi-dimensional features, construct logistic regression and fault tree analysis models, optimize and weightedly fuse the model output through K-fold cross-validation, combine the worst-case signal ranging error of the satellite to perform risk allocation, construct a satellite exclusion mechanism and introduce protection level calculation.
It achieves accurate identification of ambiguity errors with a fixed probability and reasonable allocation of risks, improving the integrity assurance capability of the PPP-AR system. It is suitable for safety-critical positioning applications with multiple constellations, multiple frequencies, and high reliability requirements.
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Abstract
Citation Information
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