GNSS Triple Frequency PPP Ambiguity Resolution
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Solution Overview
Problem
Current Precise Point Positioning (PPP) ambiguity resolution methods using Global Navigation Satellite Systems (GNSS) triple frequency signals face challenges in achieving rapid and reliable ambiguity resolution, especially in noisy conditions and multipath environments, with existing methods requiring several minutes to converge and being insufficient for real-time applications.
Innovation Solution
The method involves computing an L1/L2 or L2/L5 wide-lane fractional bias model, splitting the bias into direction-independent and direction-dependent components, and applying a carrier smooth carrier function to resolve measurement noise, allowing for instantaneous ambiguity resolution of L2/L5 and L1/L2 wide-lane ambiguities using geometry-free and geometry-based approaches, respectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional PPP ambiguity resolution methods are used, then positioning accuracy can be achieved, but convergence time is too long (several minutes) for real-time applications
Solution Approach 1:
The patent segments the bias into direction-independent and direction-dependent components, allowing separate processing and resolution of different bias sources. This segmentation enables faster convergence by addressing each component independently rather than treating all biases uniformly, thus resolving the contradiction between accuracy and convergence time.
Solution Approach 2:
The patent applies preliminary bias modeling and correction using the segmented bias components before performing ambiguity resolution. By pre-processing and correcting for biases in advance, the method reduces the time required for ambiguity convergence while maintaining positioning accuracy, directly addressing the real-time application requirement.
2Reliability
If bias is not segmented into direction-independent and direction-dependent components, then processing is simpler, but ambiguity resolution reliability is reduced in noisy conditions and multipath environments
Solution Approach 1:
The patent divides the bias into direction-independent and direction-dependent components, enabling more reliable ambiguity resolution by separately modeling different bias sources. This segmentation improves reliability in noisy and multipath conditions while keeping the computational complexity manageable through systematic processing of each component.
Solution Approach 2:
The patent applies different processing approaches to different bias components based on their characteristics. Direction-independent biases are handled differently from direction-dependent biases, allowing optimized processing for each type and improving overall reliability without uniformly increasing complexity across all processing steps.
3Measurement precision
If measurement noise is not corrected, then processing is faster, but positioning accuracy deteriorates in noisy conditions and multipath environments
Solution Approach 1:
The patent applies preliminary noise correction using the segmented bias model before final ambiguity resolution and positioning calculation. By correcting measurement noise in advance, the method ensures high positioning accuracy while maintaining efficient processing speed in the subsequent steps, resolving the contradiction between accuracy and productivity.
Data Source
AI summary
Methods and systems for performing Precise Point Positioning (PPP) ambiguity resolution using Global Navigation Satellite Systems (GNSS) triple frequency signals are described. In an embodiment, the method may include computing, using a processing device, an L1/L2 or L2/L5 wide-lane fractional bias model, in which the bias is split into one direction-independent and three direction-dependent bias components for each satellite. Additionally, the method may include resolving, using the processing device, PPP ambiguity using triple-frequency signals. The method may also include applying, using the processing device, a carrier smooth carrier function to resolve measurement noise. Resolving the PPP ambiguity may include fixing the L2/L5 wide-lane ambiguities in a geometry-free function. Additionally, resolving the PPP ambiguity may include fixing the L1/L2 wide-lane ambiguities in a geometry-based function. Similarly, resolving the PPP ambiguity may also include fixing the L1/L5 wide-lane ambiguities in a geometry-based function.