Satellite Signal Attenuation and Kalman Filtering for Rain Estimation
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Solution Overview
Problem
Existing methods for estimating rain, such as rain gauges, meteorological radars, and satellite observations, suffer from spatial representativeness, high costs, installation challenges, and accuracy issues, making them unsuitable for precise and localized rain measurement.
Innovation Solution
A method that converts total attenuation measurements of satellite signals into rain intensity using a two-layer tropospheric model and Kalman filters to provide precise, localized rain estimates, accounting for atmospheric disturbances and using historical data for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If rain gauges are used for measurement, then measurement precision is improved, but spatial representativeness deteriorates due to local validity only
Solution Approach 1:
The patent combines multiple satellite observation systems (meteosat, nos, himawar, goms) with different spectral bands and measurement capabilities to create a comprehensive rain estimation system that maintains both precision and spatial representativeness across large domains
Solution Approach 2:
The invention creates a universal rain estimation method that works across different satellite platforms, spectral bands (visible, near-infrared, infrared), and geographic regions, providing both local precision and areal representativeness through multi-functional satellite data processing
2Area of stationary object
If meteorological radars are deployed, then spatial coverage is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent uses satellite observations as a remote copy of radar-like precipitation detection, processing satellite radiometric data to infer rain properties without deploying physical radar infrastructure, thereby achieving wide spatial coverage with reduced complexity
Solution Approach 2:
The invention replaces the mechanical radar system (active electromagnetic transmission and reception) with passive satellite radiometric measurements processed through atmospheric radiation models, eliminating the need for complex radar hardware while maintaining precipitation detection capability
3Area of stationary object
If satellite observations are used, then spatial coverage is improved, but measurement precision deteriorates due to spatial errors
Solution Approach 1:
The patent segments the atmosphere into distinct layers (troposphere, stratosphere) and further divides the troposphere into sub-layers based on temperature profiles, processing satellite measurements at different altitudes and spectral bands separately to improve precision while maintaining areal coverage
Solution Approach 2:
The invention adds vertical dimension analysis by processing satellite data at multiple altitude levels and spectral bands, transforming 2D satellite imagery into 3D atmospheric structure information to enhance measurement precision without sacrificing spatial coverage
4Measurement precision
If rain gauges are installed, then measurement accuracy is improved, but installation and maintenance costs increase
Solution Approach 1:
The patent utilizes satellite systems that automatically provide rain estimation data without requiring local installation, maintenance, or operation of ground-based instruments, making the service self-providing and eliminating recurring costs while maintaining measurement accuracy
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
Enables precise, localized rain measurement with high accuracy, overcoming the limitations of existing methods by providing reliable and cost-effective rain estimation.
Implementation Method 1
measuring an instantaneous value of the ratio between the satellite signal energy and the noise power spectral density at the output of a receiver at the receiving station, the measured ratio being lower than a minimum value of instantaneous ratio equal to the minimum value only in presence of a precipitation along the satellite station section
Data Source
Figure 1
AI summary
It is provided a method for estimating the presence of rain characterized by comprising the steps of entering a set of static parameters, entering a set of dynamic parameters, measuring an instant value, sending said values to a first Kalman filter and to a second Kalman filter and define the start of a precipitative event if a difference between said KalmanST output and said KalmanFT output exceeds said "epsilonStart" threshold value and also define the term of a precipitative event if a difference between said KalmanST output and said KalmanFT output is lower than said "epsilonStop" threshold value.