GPS Atmospheric Parameter Estimation and Error Correction
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Solution Overview
Problem
Current weather prediction and climate modeling systems face limitations in accuracy and data coverage due to reliance on sparse and error-prone measurements from satellites, weather balloons, and ground stations, necessitating improved data gathering and processing methods.
Innovation Solution
The use of a network of GPS-enabled devices to collect and process data for determining atmospheric parameters like water vapor content, temperature, and pressure, with a central processor that corrects for GPS measurement errors using Kalman or sparse information filters, enabling simultaneous estimation of signal propagation velocity and position errors to refine climate and weather models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sparse measurements from satellites, weather balloons, and ground stations are used, then device complexity is reduced, but measurement precision and data coverage deteriorate
Solution Approach 1:
The patent repurposes GPS devices, originally designed for position determination, to simultaneously measure atmospheric parameters such as water vapor content, temperature, and pressure. By making the GPS receivers multi-functional, the system achieves high measurement precision without adding dedicated atmospheric sensing equipment, thus avoiding increased device complexity
Solution Approach 2:
The patent utilizes the existing GPS signal infrastructure and processing capabilities to serve dual purposes: position determination and atmospheric monitoring. The GPS receivers use their own transmitted signals to probe the atmosphere, eliminating the need for separate measurement systems and reducing overall system complexity while improving measurement precision
2Measurement precision
If a large number of GPS devices are deployed to improve data coverage, then measurement precision improves, but the complexity of error correction and data processing increases
Solution Approach 1:
The patent combines the atmospheric parameter estimation process with the GPS position solution process into a single integrated estimation framework. By merging these functions, the system processes both position and atmospheric data simultaneously using the same computational infrastructure, avoiding the need for separate complex processing systems
Solution Approach 2:
The patent implements an iterative estimation process where initial atmospheric parameters are used to correct GPS positions, which in turn improve atmospheric parameter estimates. This feedback loop continuously refines both position and atmospheric measurements, achieving high precision without requiring overly complex external processing systems
3Productivity
If GPS position error correction is performed separately from atmospheric parameter estimation, then measurement precision may be maintained, but productivity and processing efficiency deteriorate
Solution Approach 1:
The patent merges GPS position error correction and atmospheric parameter estimation into a unified processing framework. Both functions are performed simultaneously through a single estimation algorithm that solves for position, atmospheric parameters, and signal propagation velocity together, dramatically improving processing efficiency without sacrificing measurement precision
Solution Approach 2:
The patent performs atmospheric parameter estimation and position correction in an integrated preliminary processing step before final analysis. By preparing both corrected positions and atmospheric parameters simultaneously in advance, the system improves overall processing efficiency and enables faster downstream applications
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy and coverage of climate modeling and weather forecasting by leveraging a large number of GPS devices to correct errors and estimate atmospheric parameters across vast areas, improving the precision of weather predictions and climate modeling.
Implementation Method 1
determining atmospheric parameters such as water vapor content, temperature and pressure... estimating, at the central processor, a propagation velocity of one or more signals received at each of the GPS-enabled devices from one or more GPS satellites
Data Source
AI summary
Systems and methods described herein include improved data gathering, climate modeling and weather forecasting techniques. In particular, the systems include using Global Positioning System (GPS) measurements obtained from a network of GPS devices for simultaneously determining atmospheric parameters such as water vapor content, temperature and pressure, and correcting for errors in the GPS measurements, themselves. The systems and methods described herein include a central processor for receiving data from a plurality of GPS devices and updating a computerized climate or weather forecasting model. Advantageously, by using data from a plurality, and in some embodiments a very large number of GPS devices, the systems and methods described herein may solve for both propagation velocity of electromagnetic signals through the atmosphere (used for calculating atmospheric parameters useful in climate modeling) and GPS position error values (used for error correction at each GPS device).