Article Details

Abstract

To address the issues of low positioning accuracy and poor continuity caused by building obstruction and multipath effects on BeiDou/GNSS satellite signals in urban canyon environments, a BeiDou/GNSS–INS–visual multi-source fusion-enhanced positioning method is proposed. A three-tier architecture of “perception–fusion–application” is constructed, and an adaptive Kalman filtering algorithm based on signal quality assessment is designed to achieve optimal fusion of multi-source data. Experiments demonstrate that the proposed method effectively suppresses multipath effects in BeiDou/GNSS single-point positioning, stably achieving horizontal positioning errors better than 0.8 m and vertical positioning errors better than 1.2 m, with positioning continuity reaching 98.7%. It maintains high positioning accuracy even under 10 s of satellite signal obstruction, providing technical support for high-precision applications such as urban surveying.

Keywords

BeiDou/GNSS; multi-source fusion; enhanced positioning; urban canyon; performance optimization; Kalman filtering

References

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About the authors

Cai Zuzheng (1991.01-), male, Han ethnicity, from Taizhou, Zhejiang Province, is a surveying and mapping engineer with a bachelor's degree. His research interests include engineering surveying, boundary and real estate surveying, photogrammetry, and data processing in geographic information surveying and mapping.