The real time kinematic of global positioning system (GPS-RTK) provides precise positioning for bridge deformation monitoring and monitoring bridge health status. In order to solve the problem that the satellite signal is vulnerable to the influence of the positioning environment when monitoring bridges in the valleys and urban buildings, and the problem that Kalman fusion algorithm is difficult to detect the divergence caused by interruption or wrong data. This paper proposes an improved Kalman filter fusion position method based on the BD/GPS fusion positioning. This improved algorithm introduces the environmental information. The confidence level is calculated with membership function by defining the confidence region of sensor, so as to the fusion weight coefficient is determined. This paper analyzes the performance of BD/GPS positioning in bridge monitoring through comparing the traditional fusion method with the improved fusion method. Experiments show that the improved algorithm eliminates the problem of error divergence; the average number of visible satellites in BD/GPS fusion positioning is increased by 7 compared with that of GPS single system positioning, the GDOP value is reduced by 21.83%, and the positioning error is reduced by 2.51 cm. The feasibility of all-weather monitoring in the mountains, buildings and other areas is verified, and millimeter accuracy is provided, which greatly improves the performance of bridge deformation monitoring.
Supported by Supported by the National High Technology Research and Development Program (“863” Program) of China (2013AA12A206)
Cite this article:
Xiulin QIU,Qinghua LIU,Ru LI. High-precision Positioning and Deformation Monitoring Analysis of BD/GPS Based on Improved Kalman Filter Fusion[J]. Journal of Systems Science and Information, 2019, 7(3): 270-282.
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