BeiDou/GPS Displacement Detection Using Robust Weighting Based on Moving Window

doi:10.11947/j.AGCS.2016.F028

Abstract

Abstract:

The positioning accuracy of Kalman model under creep deformation condition is closely related to the observation variance, which can be affected by the accuracy of weight ratio of GPS and BDS observations. To improve displacement detection accuracy, shorten convergence time of initial coordinate and reduce monitoring cost, firstly the BDS/GPS single-frequency single-difference combination model is set up by using clock-synchronized dual-antenna BDS/GPS receiver. Then the equivalent weights of GPS and BDS observations are robustly determined respectively, and the Helmert variance component estimated by introducing time-correlated forgetting factor is used to achieve the precise weight ratio between GPS and BDS observations. Finally the coordinates are calculated using the extended Kalman filter by updating observed variance in real-time. According to the experiment, for the short baseline (1 km), BDS/GPS robust precise weighting Kalman method can shorten convergence time of initial coordinate significantly, which is suitable for monitoring the deformation body with creep characteristics, and the displacement detection accuracy can reach sub-millimeter level. Moreover the displacement convergence rate is inversely related to the length of moving window approximately.

Key words: BDS, GPS, single-frequency single-difference positioning model, robust precise weighting, displacement detection, sub-millimeter accuracy

CLC Number:

P228

ZHANG Yunlong, YANG Songlin, LUO Xiaoyan, FANG Jianhong, QIU Dongwei. BeiDou/GPS Displacement Detection Using Robust Weighting Based on Moving Window[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(S2): 72-81.

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