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GNSS-R sea surface wind speed inversion method and system based on particle swarm algorithm

A particle swarm algorithm and wind speed inversion technology, which is applied in the fields of electronics, information and atmospheric science, can solve the problems of small inversion accuracy of wind speed, large amount of calculation, complex waveform simulation, etc., to achieve improved inversion accuracy, simple model, The effect of simple structure

Active Publication Date: 2021-03-02
WUHAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0006]The purpose of the present invention is to solve the problem that the existing multi-eigenvalue combination inversion of wind speed has a small improvement in accuracy, and overcome the large amount of calculation and the waveform in the waveform matching method. Simulate complex issues such as

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  • GNSS-R sea surface wind speed inversion method and system based on particle swarm algorithm
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  • GNSS-R sea surface wind speed inversion method and system based on particle swarm algorithm

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Embodiment 1

[0064] Embodiment 1 of the present invention provides a kind of GNSS-R sea surface wind speed inversion method based on particle swarm algorithm, mainly comprises the following steps:

[0065] The first step is to download and save the dataset. Batch download the GNSS-R data and wind speed data of the specified date and save them in the specified database;

[0066] The second step is data preprocessing and data set matching. Preprocess the wind speed data set, and interpolate and match the CYGNSS data (CYGNSS data is a kind of satellite-borne GNSS-R data) and wind speed data according to space and time;

[0067] In the third step, the experimental data set is generated. According to the preset data filtering conditions, the matching data set is screened and formatted, and then the training set and the test set are divided according to a certain proportion;

[0068] The fourth step is to train the wind speed inversion model. Construct the DDM eigenvalue, the signal incidenc...

Embodiment 2

[0116] In another embodiment 2 of the present invention, a kind of GNSS-R sea surface wind speed retrieval system based on particle swarm algorithm is also provided, specifically comprising:

[0117] The data download and storage module is used to download GNSS-R data and wind speed data and store them in the storage medium;

[0118] The data preprocessing module is used to preprocess the data and perform spatiotemporal matching on the two data sets;

[0119] The data set generation module is used to screen and quality control the matched data sets, integrate data formats, and divide training sets and test sets;

[0120] The inversion model generation module is used to construct a single eigenvalue geophysical model function, complete the single eigenvalue inversion, and then use the particle swarm algorithm to optimize the combination of the single eigenvalue inversion results to obtain the optimal combination coefficient, and then pass the test The feasibility of the model ...

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Abstract

The invention discloses a GNSS-R sea surface wind speed inversion method and system based on a particle swarm algorithm, and belongs to the fields of electronics, information, atmospheric science andthe like. The method comprises the following steps: downloading and storing GNSS-R data and sea surface wind speed data in batches; preprocessing the data, and completing space and time matching of the GNSS-R data and the wind speed data; screening the matched data, reserving high-quality samples, then performing data set file format normalization, and randomly dividing a training set and a test set; taking the DDM characteristic value and the signal incident angle as input, constructing a geophysical mode function, and realizing single characteristic value wind speed inversion; and based on aparticle swarm optimization algorithm, optimizing a combined wind speed inversion model to obtain an optimal combined optimization coefficient, and completing wind speed combined inversion. Accordingto the method, the wind speed combination inversion is carried out by using the particle swarm algorithm, so that the accuracy and efficiency of inversion are greatly improved, and the method has thecharacteristics of simple model, high robustness, high inversion precision and the like.

Description

technical field [0001] The invention relates to the fields of electronics, information and atmospheric science, and in particular to a GNSS-R sea surface wind speed retrieval method and system based on a particle swarm algorithm. Background technique [0002] As an important meteorological parameter, the sea surface wind field indirectly affects the earth's climate through the ocean circulation, so it is of great significance to accurately detect and study it. The traditional sea surface wind field detection methods include stations, buoys, and meteorological remote sensing satellites, etc., which have defects such as limited measurement range, high cost, and high power consumption. In recent years, the theory of sea surface wind speed retrieval by GNSS-R technology has been continuously improved and developed, providing a sea surface wind field detection method with large coverage, high temporal and spatial resolution, and low cost. At present, there are mainly two methods...

Claims

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Application Information

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IPC IPC(8): G01S19/14G06N3/00G06F16/29G06F16/245
CPCG01S19/14G06N3/006G06F16/29G06F16/245Y02A90/10
Inventor 郭文飞杜皓郭迟叶世榕
Owner WUHAN UNIV
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