Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Rapid processing method and system for whole large scale GNSS network data

A processing method and large-scale technology, applied in radio wave measurement systems, satellite radio beacon positioning systems, instruments, etc., can solve the problems of inconsistent results, low data processing efficiency, reduced analysis accuracy and reliability, etc. Improve data continuity, stable and reliable network-wide solution results, and high-precision network-wide solution results

Inactive Publication Date: 2016-02-03
WUHAN UNIV
View PDF4 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in order to combine the subnetworks together, there must be a certain number of public observation stations between the subnetworks. Since these public stations are used twice or more, the final variance covariance matrix obtained by it is different from that of the direct whole network solution. The results are not completely consistent, which may reduce the precision and reliability of subsequent analysis
Therefore, it is very meaningful to study a high-efficiency GNSS data processing method to solve the problem of low data processing efficiency in large-scale GNSS networks.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Rapid processing method and system for whole large scale GNSS network data
  • Rapid processing method and system for whole large scale GNSS network data
  • Rapid processing method and system for whole large scale GNSS network data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0080] See figure 2 , the present embodiment selects the data of about 460 IGS reference stations globally distributed from 201 days to 289 days in 2012, wherein about 100 globally uniformly distributed stations are selected as reference stations, see figure 2 The middle triangle mark is used to calculate the initial precision orbit, the initial precision clock difference and the initial undifferenced floating-point ambiguity. In this embodiment, a computer equipped with a CPUi7 (2.6GHZ) processor, 16GB internal memory, and MACOS 10.8 system is used for data processing.

[0081] The data processing flow is as follows:

[0082] Step 1, use the data of the reference station network to determine the orbit, and obtain the satellite's precise orbit, precise clock error and undifferenced floating-point ambiguity.

[0083] Step 2, take the undifferenced floating-point ambiguity obtained in step 1 as the initial undifferenced floating-point ambiguity, use the reference station net...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a rapid processing method and system for whole large scale GNSS network data. The rapid processing method comprises: the step 1: utilizing a whole network solution to perform orbit determination for the reference station network data; the step 2: evaluating the wide lane UPD and the narrow lane UPD of a satellite end according to the reference station network data; the step 3: performing PPP positioning and ambiguity fixing one by one for the observation stations in the GNSS network; the step 4: converting the phase observation value into a high precision distance observation value; and the step 5: performing whole network solution for the GNSS network according to the high precision distance observation value. For the rapid processing method and system for whole large scale GNSS network data, as the ambiguity is fixed during the single-station solution process, the whole network solution has no need for evaluating the unfixed ambiguity parameter or only needs to evaluate the unfixed ambiguity parameter so the parameters to be evaluated can be greatly reduced and the calculating efficiency can be improved. Therefore the large scale GNSS network data can be solved at the same time. And at the same time, the rapid processing method and system for whole large scale GNSS network data can improve the data continuity and can provide the whole network solution result with stability, reliability and high precision.

Description

technical field [0001] The invention belongs to the technical field of satellite navigation positioning and application, and in particular relates to a method and system for rapid overall processing of large-scale GNSS network data. Background technique [0002] With the continuous popularization and application of satellite navigation and positioning satellite system (GNSS) and the construction and development of new satellite systems, there are more and more ground GNSS tracking stations, such as IGS (Beutler et al., 1994b; Dowe et al., 2009) global tracking network measurement There are 460 stations (Neilan et al., 2013), nearly 2000 national CORS stations in the United States (Snay and Soler, 2008), more than 1300 stations in Japan’s earthquake monitoring network (Sagiya et al., 2004), and China’s CORS stations There are far more than 1000 (Dangetal., 2011). Unified processing of the data of all stations and satellites at the observation value level (hereinafter referre...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G01S19/44
CPCG01S19/44
Inventor 姜卫平陈华葛茂荣周晓慧
Owner WUHAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products