Parallel Robust Estimation for Large-scale High-precision GNSS Baseline Vector Network

doi:10.11947/j.AGCS.2015.20140154

Abstract

Abstract:

According to the characteristics of large-scale GNSS baseline vector network, the relevant observations robust estimation model which is based on RECO scheme is improved by parallel computing. A feasible process steps are also presented. Using the improved model, a numerical example is given. It is demonstrated that the large-scale GNSS baseline vector related robust parallel estimation not only can inhibit the influence of the outliers to the parameter estimates, but also significantly improve the computational efficiency.

Key words: dependent robust estimation, GNSS, baseline vector network, equivalent weight matrix, parallel estimation

CLC Number:

P228

CUI Yang, LÜ Zhiping, ZHANG Youyang, LI Linyang. Parallel Robust Estimation for Large-scale High-precision GNSS Baseline Vector Network[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(5): 495-502.

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