Satellite Positioning Integer Solution via Posterior Weighted Probability
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Solution Overview
Problem
Current methods for obtaining integer solutions in satellite positioning are time-consuming, unreliable, and prone to falsification, struggling to balance initialization time and positioning accuracy.
Innovation Solution
A method that synthesizes multiple integer vectors based on a given reliability probability to constrain and solve for satellite positioning parameters, using a posterior weighted probability to compute integer solutions and their variance matrices, thereby reducing initialization time and enhancing reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional integer solution methods are used to ensure reliability, then positioning reliability is improved, but initialization time increases significantly
Solution Approach 1:
The patent segments the integer solution process into two distinct phases: a fast estimation phase that quickly generates candidate integer solutions without strict reliability constraints, and a verification phase that checks these candidates against reliability criteria. This segmentation allows the system to achieve fast initialization while maintaining positioning reliability through the verification step.
Solution Approach 2:
The patent applies partial action by performing verification only on the most promising candidate solutions rather than exhaustively verifying all possible integer solutions. By focusing verification resources on a select few candidates based on their estimated quality, the system achieves reliable positioning results without the time cost of complete verification.
2Reliability
If multiple checking methods are applied to verify integer solutions, then reliability is improved, but computational complexity and difficulty increase
Solution Approach 1:
The patent inverts the traditional verification approach by first generating candidate solutions through estimation and then verifying them, rather than starting with verification and only accepting solutions that pass. This inversion simplifies the process by reducing the number of candidates that need rigorous verification, thereby lowering computational complexity while maintaining reliability.
Solution Approach 2:
The patent extracts the verification step as a separate, optional phase that applies to only the most promising candidates. By taking out verification from the main solution generation flow and applying it selectively, the system reduces overall computational complexity while still ensuring reliability when needed.
3Measurement precision
If whole cycle ambiguity identification is performed to ensure accuracy, then positioning precision is improved, but initialization time increases
Solution Approach 1:
The patent performs preliminary action by generating candidate integer solutions through fast estimation methods before applying verification or refinement. This preliminary estimation provides a head start that reduces the time needed for subsequent verification steps, achieving both speed and precision by doing the heavy lifting of candidate generation first.
Data Source
AI summary
The present disclosure discloses a method for quickly acquiring a highly reliable integer solution for satellite positioning. The method includes: acquiring observation data by a data computing platform from a GNSS receiver; establishing a GNSS carrier observation equation; solving a real solution for ambiguity and the corresponding variance matrix, a real solution for other unknown parameters including positioning parameters and the corresponding variance matrix, and a covariance matrix of the and by using the least squares method; determining integer vectors with the same dimension as the ambiguity according to a given reliability probability; computing a posterior weighted probability with the integer vectors being the true value of the ambiguity; computing an integer solution for other unknown parameters including positioning parameters by using the posterior weighted probability; computing a variance matrix of the integer solution for other unknown parameters; and outputting a computed result by the data computing platform.