GPS Gravity Model for GLONASS State Vector Extrapolation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current satellite navigation systems face challenges in accurately and reliably using satellite state information from multiple systems, such as GPS and GLONASS, due to differences in data formats and orbital inclinations, which can lead to reception issues and inaccurate position computation, especially in urban environments.
Innovation Solution
The method involves using GPS extended ephemeris functionality to produce satellite state vector estimates for GLONASS satellites, which can be combined with GPS satellite vectors, and extrapolating GLONASS satellite position and trajectory information using a GPS gravity model, allowing for more accurate and longer-term predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GLONASS satellite state information is processed using its own system models, then the processing can be performed, but the accuracy and validity of the satellite state predictions are limited due to different orbital inclinations and data formats
Solution Approach 1:
The patent uses GPS satellite state vectors and GPS gravity models as intermediaries to represent and process GLONASS satellite information. The GPS ephemeris data serves as a mediator that allows the receiver to accurately compute GLONASS satellite positions and trajectories without requiring separate processing for each satellite system, thereby resolving the compatibility issue while maintaining high prediction accuracy.
Solution Approach 2:
The patent makes the GPS receiver capable of handling both GPS and GLONASS satellite systems using a unified processing approach. The receiver uses universal GPS-based models and algorithms to process GLONASS data, allowing a single receiver design to support multiple satellite systems without requiring system-specific processing chains for each constellation.
2Measurement precision
If current ephemeris data is used for position computation, then fast and accurate position estimation is achieved, but the data must be frequently updated which increases processing complexity and time requirements
Solution Approach 1:
The patent pre-computes and stores GPS satellite state vectors and gravity models in the receiver before actual positioning is needed. This preliminary preparation allows the receiver to immediately use accurate ephemeris data without requiring time-consuming data downloads or computations at the moment of first fix, significantly reducing Time-To-First-Fix while maintaining high position estimation accuracy.
3Reliability
If multiple satellite systems with different orbital inclinations are processed together, then coverage and reliability are improved, but reception issues and computation inaccuracies occur due to data format differences
Solution Approach 1:
The patent transforms GLONASS satellite state parameters into GPS-compatible formats by converting orbital elements and using GPS gravity models for trajectory computation. This parameter transformation allows the receiver to uniformly process both GPS and GLONASS data using the same processing algorithms, reducing computational complexity while maintaining the reliability benefits of multi-system processing.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
The present invention is related to location positioning systems, and more particularly, to a method and apparatus for using satellite state information from two or more different satellite systems in navigation processing. According to one aspect, it makes use of GPS extended ephemeris functionality to produce satellite state vector estimates for GLONASS satellites. These satellite state vector estimates can be used alone or in combination with GPS satellite vectors to provide updates to the receiver's navigation processing. According to further aspects, the GLONASS satellite position and trajectory information is extrapolated with a GPS gravity model rather than the GLONASS model, thereby allowing it to be extrapolated more accurately and for longer periods of time than the GLONASS model allows.