GNSS multipath effect correction method based on BP neural network technology

A BP neural network and multipath effect technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as the difficulty of accurately modeling multipath errors and the inability to calculate and solve multipath effects in real time

Active Publication Date: 2019-05-10
HUNAN LIANZHI BRIDGE & TUNNEL TECH
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Problems solved by technology

[0008] The purpose of the present invention is to provide a GNSS multipath effect correction method based on BP neural network technology, to solve the complex m

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  • GNSS multipath effect correction method based on BP neural network technology
  • GNSS multipath effect correction method based on BP neural network technology
  • GNSS multipath effect correction method based on BP neural network technology

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[0052] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings, but the present invention can be implemented in various ways defined and covered by the claims.

[0053] A kind of GNSS multi-path effect correction method based on BP neural network technology provided by the present invention is implemented on the basis of BP neural network technology application, and BP neural network algorithm includes an input layer, a hidden layer and an output layer (see figure 1 ), where the number of neurons in the input layer is twice the number of common satellites of the reference station and the monitoring station, and the output layer has three neurons, which are the time series of coordinates in the X, Y, and Z directions of the monitoring point; the BP neural network activates The function adopts the Sigmoid function:

[0054]

[0055] A kind of GNSS multi-path effect correction method based on BP neural network tech...

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Abstract

The invention provides a GNSS multipath effect correction method based on a BP neural network technology. The method sequentially comprises the following steps of multipath error extraction, sample pre-selection, sample preprocessing, sample training, network topology determination, data storage, data post-processing and model updating, wherein modeling is carried out on multipath errors by meansof forward propagation of signals and reverse propagation of the errors of a BP neural network algorithm, a motion condition of a satellite, a satellite elevation, a signal-to-noise ratio and multipath effect errors caused by ambient conditions around monitoring points can be effectively weakened, and meanwhile, periodic fluctuations in directions X, Y and Z of a monitoring station are remarkablyimproved through trained results, a model is dynamically updated according to the new multipath error data, and the periodic errors caused by multipath effects on the monitoring points can be weakenedto the maximum extent.

Description

technical field [0001] The invention relates to the technical field of multipath effects, in particular to a method for correcting GNSS multipath effects based on BP neural network technology. Background technique [0002] GNSS (Global Navigation Satellite System) is a general term for various navigation systems, including: GPS, BDS, GLONASS, Galileo and other navigation systems. With the rapid development of satellite navigation systems, GNSS technology has been widely used in various fields such as navigation, deformation monitoring, positioning, and timing. GNSS has been widely used in deformation monitoring because of its all-weather, fully automatic, and no manual intervention. [0003] GNSS uses short baseline relative positioning technology in deformation monitoring to obtain the deformation of the monitored object in real time. Due to the short baseline, most of the errors have been effectively eliminated by filtering and differential technology. However, multipath...

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Application Information

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IPC IPC(8): G01S19/42G01B7/16G06N3/04G06N3/08
Inventor 梁晓东雷孟飞孔超杨振武
Owner HUNAN LIANZHI BRIDGE & TUNNEL TECH
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