Partial Ambiguity Fixing for High-Integrity GPS Navigation
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Solution Overview
Problem
In GPS-based navigation systems like JPALS, achieving high integrity and accuracy is challenging due to low probability of correct fix (PCF) and high protection levels, especially when using integer bootstrapping or LAMBDA algorithms, which can lead to lower PCF and higher protection levels, affecting availability and accuracy.
Innovation Solution
A system that decorrelates GPS carrier phase integer ambiguities using LAMBDA algorithms and partially fixes ambiguities in the LAMBDA domain, generating a partial almost-fix solution (PAFS) based on a Probability of Almost Fix (PAF) and protection levels, allowing for dynamic updating and reverting to float ambiguities when thresholds are met.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If integer bootstrapping or LAMBDA algorithms are used to fix carrier phase integer ambiguities, then accuracy is improved, but probability of correct fix decreases and protection levels increase
Solution Approach 1:
The patent segments the ambiguity fixing process into two distinct phases: (1) LAMBDA decorrelation phase that transforms ambiguities to reduce correlation and improve fix probability, and (2) Bootstrapping phase that fixes ambiguities sequentially from most to least certain. This segmentation allows each algorithm to operate in its optimal domain, resolving the contradiction between accuracy and reliability.
Solution Approach 2:
The LAMBDA decorrelation is performed as a preliminary action before bootstrapping. By pre-processing the ambiguities through LAMBDA to reduce correlation, the subsequent bootstrapping process operates on already-optimized data, improving both the probability of correct fix and maintaining high accuracy without requiring full LAMBDA complexity.
2Reliability
If LAMBDA algorithms are used to decorrelate ambiguities prior to fixing, then probability of correct fix increases and protection levels decrease, but device complexity increases
Solution Approach 1:
The patent applies LAMBDA decorrelation partially - only to the extent necessary to improve bootstrapping performance, rather than performing complete LAMBDA fixing. The decorrelated ambiguities are then passed to bootstrapping which handles the actual fixing. This partial application of LAMBDA reduces computational complexity while maintaining the reliability benefits.
Solution Approach 2:
LAMBDA decorrelation serves as an intermediary step between raw float ambiguities and the bootstrapping fixing process. It transforms the input data into a more favorable form for bootstrapping without performing the complete fixing operation itself, thus reducing overall system complexity while improving reliability.
3Reliability
If partial ambiguity fixing is used to maintain probability of correct fix, then availability improves, but manufacturing precision of navigation solution decreases
Solution Approach 1:
The patent implements a dynamic ambiguity fixing strategy where the system adaptively determines the optimal number of ambiguities to fix based on real-time conditions. The bootstrapping process naturally fixes ambiguities in order of certainty, dynamically adjusting the fix solution to maximize availability while maintaining the highest possible accuracy for the fixed subset.
Solution Approach 2:
The system changes the parameter of ambiguity fixing completeness dynamically. Rather than always fixing all ambiguities or none, it fixes a variable number of ambiguities based on their individual fix probabilities and the resulting impact on protection levels. This parameter change allows optimization of both availability and accuracy in real-time.
Data Source
AI summary
A system and for determining precision navigation solutions decorrelates GPS carrier-phase ambiguities derived from multiple-source GPS information via Least-squares AMBiguity Decorrelation Adjustment (LAMBDA) algorithms. The set of decorrelated floating-point ambiguities is used to compute protection levels and the probability of almost fix (PAF), or the probability that the partial almost-fix solution corresponding to the decorrelated ambiguities is within the region of correctly-fixed or low-error almost-fixed ambiguities. While the PAF remains below threshold and the protection levels remain below alert levels, the optimal navigation solution (floating-point, partial almost-fix, or fully fixed) is generated by fixing the decorrelated ambiguities are one at a time in the LAMBDA domain and replacing the appropriate carrier-phase ambiguities with the corresponding fixed ambiguities, reverting to the last solution if PAF reaches the threshold or if protection levels reach the alert levels.