Improved stacking filtering method considering multiple weighting factors

doi:10.13474/j.cnki.11-2246.2023.0207

Abstract

Abstract: Aiming at the issue that correlation between stations is often neglected when extracting the common mode error of regional GNSS time series, this paper proposes an improved stacking filtering method which considers multiple weighting factors such as correlation coefficient and distance factor on the basis of existing research on stacking filtering, and analyzes the applicability of the method by selecting data from stations in Shanxi province. The results show that using the improved stacking filtering method in this paper, the root mean square of the coordinate residual time series is reduced by 48.53%, 39.42% and 48.61% on average in the N, E and U components, and the effect of the filtering on the velocity in the N and E directions is 0.5 mm/a and 1 mm/a in the U direction, and Compared with regional superposition filtering, this improved method further reduces the root-mean-square of the residual time series by 20%～40% and can extract the common mode error more accurately, which can provide fine and reliable data support for the study of the mechanism of regional crustal motion and dynamics.

Key words: distance factor, correlation coefficient, GNSS time series, common-mode error, improved stacking filter

CLC Number:

P228

LI Xiaotong, LI Wei, XIE Xukang, HUANG Yutong. Improved stacking filtering method considering multiple weighting factors[J]. Bulletin of Surveying and Mapping, 2023, 0(7): 91-96.

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