A method for extracting generalized common mode error of GPS time series

Abstract

The invention discloses a GPS time sequence generalized common mode error extraction method. According to the invention, space responses of common mode errors are analyzed, an extraction mechanism of large-area GPS network common mode errors is established, physical factors such as a correlation coefficient [rho], the distance, latitude and longitude, a local effect, a load effect, a main component contribution rate and space responses are used as evaluation factors, , a feasible estimation method is provided to the common mode errors between stations of the large-area large-scale GPS network by means of clustering analysis, and a better filtering effect is obtained; in addition, the limitation of a conventional GPS time sequence model is considered, the model errors introduced in time sequence annual and semiannual term fitting processes are weakened, the periodicity of the common mode errors is considered, and that is to say, before common mode error removing is carried out on a residual sequence, the annual and semiannual terms of an original coordinate sequence are reserved, so that the space changes and the periodical change of the common mode errors are practically reflected, and a basis is further provided for improving the precision of a GPS coordinate sequence model.

Description

technical field [0001] The invention belongs to the technical field of continuous operation global positioning and navigation systems, and relates to a method for extracting GPS time series generalized common mode errors. Background technique [0002] With the improvement of the positioning accuracy of the satellite positioning system, the continuously running GPS (Global Positioning System) tracking stations distributed around the world have accumulated decades of observation data and obtained many valuable understandings. [0003] The time series of GPS coordinates contains not only tectonic motion signals, but also noise such as non-tectonic motion signals and seasonal signals. The mixed noise affects the reliability of GPS solutions, and may even make wrong interpretations for some geophysical phenomena. How to efficiently and quickly remove these noises and separate the influence of non-structural motion signals is one of the key issues in GPS coordinate time series. ...

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Problems solved by technology

[0005] At present, there are some defects in the separation research method of common mode error in GPS network: 1) what is the physical origin of CME, and what are the influencing factors of CME in GPS network, lack of in-depth research; 2) most of the current research on CME is limited to In a small area network, the scale of CME spatial similarity shows consistency, which directly affects the reliability of CME separation

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