Robust Parallel Bayes Estimation for Large-scale GNSS Baseline Vector Network

LI Linyang; LV Zhiping; CUI Yang; WANG Yupu; LV Hao; GONG Xiaochun

doi:10.13203/j.whugis20140763

Volume 41 Issue 10

Oct. 2016

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Geomatics and Information Science of Wuhan University > 2016 > 41(10): 1385-1390. > DOI: 10.13203/j.whugis20140763

LI Linyang, LV Zhiping, CUI Yang, WANG Yupu, LV Hao, GONG Xiaochun. Robust Parallel Bayes Estimation for Large-scale GNSS Baseline Vector Network[J]. Geomatics and Information Science of Wuhan University, 2016, 41(10): 1385-1390. DOI: 10.13203/j.whugis20140763

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Robust Parallel Bayes Estimation for Large-scale GNSS Baseline Vector Network

1.
School of Surveying and Mapping, Information Engineering University, Zhengzhou 450052, China

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The National Natural Science Foundation of China Nos. 41274015,41674019

National High Technology Research and Development Program of China No. 2013AA122501

National Key Research and Development Program of China No.2016YFB0501701

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Received Date: January 19, 2015
Published Date: October 04, 2016

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Abstract

Abstract

Based on the characteristics of large-scale GNSS baseline vector network adjustment and the IGGⅢ scheme, an improved double-factor equivalent weight with different weight-dropping efficiency schemes were derived. Methods and adaptability of parallel programming are compared, and a calculation procedure based on multi-task classification and processing is proposed and it achieves parallel estimation. Data from IGS are used in an experiment, and the results show that the proposed method not only takes full advantage of the prior information of coordinates and effectively restrains the influence of the baseline vector outliers, but also makes full use of the hardware platform, then significantly improves the computational efficiency.
- GNSS baseline vector network,
- robust Bayes estimation,
- IGGⅢ,
- parallel computing

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