RTGx GNSS Processing System Orbit Determination
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Solution Overview
Problem
Current global navigation satellite systems (GNSS) face challenges in achieving accurate and efficient real-time and post-processed orbit determination, positioning, and environmental monitoring due to limitations in processing GNSS data, particularly in correcting satellite and receiver states, and accounting for environmental impacts.
Innovation Solution
The RTGx system processes GNSS measurements to estimate high-fidelity satellite and signal models, refine orbital and clock states, and transmit improved parameters, employing advanced algorithms and software architecture capable of real-time and post-processing operations, including Kalman filters, square root information filters, and solar radiation force models, to provide accurate and reliable GNSS data products.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If advanced algorithms and software architecture are employed to process GNSS measurements, then measurement precision and orbit determination accuracy are improved, but device complexity increases
Solution Approach 1:
The processing system is divided into distinct functional modules: measurement reception module, anomaly detection module, model calculation module, parameter estimation module, and result transmission module. This segmentation allows each module to handle specific tasks independently, improving overall measurement precision while managing system complexity through modular architecture.
Solution Approach 2:
High-fidelity satellite and signal models serve as intermediaries between raw GNSS measurements and final orbit determination results. These models approximate measurements and provide a structured framework for analysis, enabling accurate orbit determination without requiring direct complex processing of all raw data.
2Productivity
If real-time processing is implemented to provide timely orbit determination, then productivity is improved, but measurement precision may deteriorate due to limited processing time
Solution Approach 1:
The system performs preliminary actions by detecting and flagging anomalous measurements and phase breaks before main processing. By pre-identifying and excluding problematic data points, the system ensures that subsequent real-time processing operates on clean data, maintaining high precision without sacrificing processing speed.
Solution Approach 2:
The processing system operates continuously with uninterrupted useful action, maintaining real-time processing capability while consistently applying anomaly detection, model calculation, and parameter estimation. This continuous operation ensures both timely results and sustained measurement precision throughout the processing period.
3Reliability
If comprehensive model parameters are estimated to account for environmental impacts, then reliability is improved, but loss of time increases due to extended processing duration
Solution Approach 1:
The system estimates multiple model parameters including satellite orbital parameters, clock states, and environmental factors. By systematically varying and optimizing these parameters, the system achieves comprehensive environmental accounting and improved reliability. The parameter estimation process efficiently manages processing time through iterative refinement rather than exhaustive analysis.
Solution Approach 2:
The system employs feedback mechanisms where estimated parameters are used to improve subsequent processing iterations. By feeding back the results of parameter estimation into the processing loop, the system progressively refines accuracy and reliability while minimizing total processing time through intelligent iteration rather than linear processing.
Data Source
AI summary
Novel methods and systems for the accurate and efficient processing of real-time and latent global navigation satellite systems (GNSS) data are described. Such methods and systems can perform orbit determination of GNSS satellites, orbit determination of satellites carrying GNSS receivers, positioning of GNSS receivers, and environmental monitoring with GNSS data.