Clustered PPP Error Estimation for Ambiguity-Fixed Navigation
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Solution Overview
Problem
Existing satellite navigation systems face challenges in determining precise satellite phase biases and atmospheric errors due to high computational burdens, limiting the accuracy and efficiency of Precise Point Positioning (PPP) without the need for raw measurements from a reference station.
Innovation Solution
A method involving clustering of receivers into groups to process undifferenced and uncombined measurements, using a Kalman filter for individual cluster solutions, and a least-square estimation for multi-cluster solutions to determine ambiguity-free phase biases and errors, allowing for efficient and accurate satellite position corrections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate individual values for phase ambiguities and errors are determined based on code and phase measurements, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the global network of receivers into multiple clusters, where each cluster independently determines local values for satellite phase biases and errors. This segmentation reduces the computational burden on any single processing unit while maintaining high measurement precision through localized analysis of code and phase measurements.
Solution Approach 2:
The patent transitions from a single global solution to a multi-dimensional approach by introducing the cluster dimension. Each cluster operates independently to determine local parameter values, and these local solutions are then combined to form a global solution, effectively adding a spatial dimension to the problem-solving approach.
2Measurement precision
If full information content from code and phase measurements is used, then measurement precision is improved, but productivity decreases
Solution Approach 1:
By dividing the receiver network into clusters, the patent enables parallel processing of measurement data across multiple independent clusters. Each cluster processes code and phase measurements to determine local satellite phase biases and errors, significantly improving processing efficiency while utilizing the full information content of the measurements.
Solution Approach 2:
The patent performs preliminary determination of satellite phase biases and errors at the cluster level before combining results globally. This preliminary action at the local level reduces the overall computational burden and improves productivity while maintaining full utilization of measurement information.
Data Source
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AI summary
A method for Precise Point Positioning in a satellite navigation system (1) is described. The satellite navigation system (1) comprises a plurality of navigations satellites (2) and a plurality of base stations (8) each provided with a receiver (7) that receives satellite signals (4) and is used for determining ambiguity-free phase biases and further instrumental and atmospheric errors wherein the errors are arranged for being transmitted to navigation devices (6) and arranged for being used by the navigation devices (6) for performing Precise Point Positioning including ambiguity fixing, the method comprising the steps: - obtaining code and phase measurements which were performed on the satellite signals (4) by the plurality of receivers (7) at two or more frequencies, - determining separate individual values for a plurality of phase ambiguities and a plurality of the errors based on the code and phase measurements, wherein - the receivers (7) are grouped into clusters (9), - in each cluster (9) a determination (16) of a single cluster solution is performed, in which satellite errors selected from the group of satellite position errors, satellite clock errors and satellite phase biases are determined based on the phase and code measurements performed by the receivers (7) of the respective cluster (9); - a determination (17) of a multi-cluster solution is performed, in which values of the selected satellite errors, which were determined in different clusters (9) are adjusted by an estimation process (33) applied to the values of the selected errors determined in different clusters.