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A Region Division Method Based on Principal Component Analysis

An area division method and principal component analysis technology, which can be used in instruments, measuring devices, calculations, etc., and can solve problems such as inability to divide areas.

Active Publication Date: 2020-08-07
WUHAN UNIV
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Problems solved by technology

[0005] The embodiment of the present invention provides a region division method based on principal component analysis, which is used to solve or at least partially solve the technical problem that the method in the prior art cannot perform accurate region division

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  • A Region Division Method Based on Principal Component Analysis

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Embodiment Construction

[0042] An embodiment of the present invention provides a region division method based on principal component analysis, which is used to improve the technical problem that accurate region division cannot be performed in the prior art.

[0043] The general idea of ​​the technical solution in the embodiment of the application is as follows:

[0044]Aiming at the fact that multiple stations in the GPS / GNSS network are affected by the same source and appear regional, the present invention provides an area division method based on principal component analysis, which performs a method for eigenvectors under the condition that the total variance remains unchanged. Linear transformation can realize the presentation of a spatial type pair of the original variable field area structure pair. The load vector of the load matrix B' can reflect the regional correlation structure of the residual time series of multiple stations under different constraint standards, so that accurate regional di...

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Abstract

The present invention provides a region division method based on principal component analysis, first obtain the coordinate time series observation value of the GNSS station, and obtain the residual coordinate time series according to the coordinate time series observation value, and then calculate the common epoch of all stations , and construct the observation sample matrix based on the public epoch, and then construct the covariance matrix B of all stations n×n , and then for the covariance matrix B n×n Orthogonal decomposition obtains the orthogonal matrix P; next, the load matrix A is obtained according to the observation sample matrix and the orthogonal matrix, the eigenvector is obtained from the orthogonal matrix P, and the corresponding K are selected according to the cumulative result of the eigenvalues ​​of the eigenvectors Accumulate eigenvectors; then reprocess the K accumulated eigenvectors, perform linear transformation on the orthogonal matrix P, and obtain the linearly changed loading matrix B' and principal component G. Finally, the linearly changed load matrix B' is analyzed to obtain the result of area division. The invention can greatly improve the accuracy of area division.

Description

technical field [0001] The invention relates to the technical field of precision processing of GNSS data, in particular to an area division method based on principal component analysis. Background technique [0002] In recent years, various GPS / GNSS (Global Positioning System Global Positioning System and Global Navigation Satellite System Global Navigation Satellite System) monitoring networks have been established at home and abroad, such as the China Crustal Movement Observation Network and the Chinese Mainland Tectonic Environment Monitoring Network, the United States PBO network, EPN in Europe, etc. The operation of these GPS / GNSS monitoring networks has produced a large amount of observation data which is increasing exponentially. These years of accumulated observation data constitute the GNSS coordinate time series. [0003] At present, the superposition algorithm is usually used in the existing technology to assume the uniformity of the spatial distribution of the ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S19/42G06K9/62
CPCG01S19/42G06F18/2135
Inventor 姜卫平周晓慧陈华
Owner WUHAN UNIV
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