Regional NWP tropospheric delay correction method based on GRNN model

A tropospheric delay and regional technology, applied in neural learning methods, biological neural network models, using multiple variables to indicate weather conditions, etc., can solve problems such as insufficient accuracy, achieve the effects of improving accuracy, wide application range, and improving performance

Active Publication Date: 2019-07-19
SHANDONG UNIV OF SCI & TECH
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Problems solved by technology

[0005] The purpose of the present invention is to correct one of the important error sources, the tropospheric delay, in order to improve the accuracy of satellite positioning, and to provide a method for correcting the tropospheric delay of regional NWP based on the GRNN model, which is used to solve the existing tropospheric delay estimation method Technical issues with insufficient precision

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  • Regional NWP tropospheric delay correction method based on GRNN model
  • Regional NWP tropospheric delay correction method based on GRNN model
  • Regional NWP tropospheric delay correction method based on GRNN model

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Embodiment

[0031] In order to prove the effectiveness of the regional NWP tropospheric delay correction method based on the GRNN model, the NCAR tropospheric data of 650 stations in Japan with a sampling rate of 2 hours in 2005 and the corresponding European mesoscale weather Forecast center (European Center for Medium-Range Weather Forecasts, referred to as ECMWF) stratified meteorological data of ERA-Interim products in the reanalysis data, its planar resolution is 0.125°×0.125°, and the vertical resolution is 37 layers (the height of the top layer is about is 47km), and the time resolution is 6 hours. The rectangular area of ​​the Japanese region is about 3 million square kilometers, and the experimental area ranges from 32°N to 40°N and 130°E to 142°E. The data of 100 stations are selected from 650 stations as GRNN training data, and the data of the remaining 550 stations are GRNN test data. The training stations are distributed as figure 2 As shown, the test station distribution ...

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Abstract

The invention discloses a regional NWP (Numerical Weather Prediction) tropospheric delay correction method based on a GRNN (General Regression Neural Network) model. According to the method, firstly,ZTD (Zenith Tropospheric Delay) in one continuous year of all selected continuous operational reference stations in an operation region and reanalysis data provided by NWP in the region in the continuous year are acquired, and an integral method is utilized to invert the ZTD of the continuous operational reference stations in the region; secondly, parts of the stations are selected to serve as training stations, the remaining stations serve as test stations, a GRNN is utilized to fit residual errors of the ZTD inverted according to NWP data of the training stations, and a GRNN residual error fitting model is obtained; and thirdly, error compensation is performed on the ZTD inverted according to the NWP data of the test stations through the GRNN residual error fitting model, and then precise NWP_ZTD of the test stations is obtained. Through the method, error compensation is performed on the NWP_ZTD by fitting the residual errors of the NWP_ZTD through the GRNN model according to the change law of the residual errors of the NWP_ZTD along with multiple meteorological factors for the first time, and NWP inverted tropospheric delay precision is improved.

Description

technical field [0001] The present invention relates to a tropospheric delay correction method, in particular to a tropospheric delay correction method based on a generalized regression neural network (General Regression Neural Network, GRNN for short) model based on a regional numerical weather prediction (NumericalWeather Prediction, referred to as NWP) model, according to the NWP_ZTD The residual error varies with various meteorological factors, and the GRNN model is used to fit the residual error of NWP_ZTD, and then the error compensation is performed on NWP_ZTD to improve the accuracy of NWP inversion of tropospheric delay, thereby improving the precise point positioning (Precise Point Positioning, PPP for short). ) and long-distance baseline real-time precise dynamic positioning (Real Time Kinematic, referred to as RTK) convergence speed and positioning accuracy, belonging to the field of global satellite navigation and positioning technology. Background technique [...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S19/40G01S19/07G01W1/02H04B17/364H04B17/391G06N3/04G06N3/08
CPCG01S19/40G01S19/07G01W1/02H04B17/364H04B17/391G06N3/08G06N3/045
Inventor 徐莹闫俐孜李雷刘凡刘国林
Owner SHANDONG UNIV OF SCI & TECH
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