In optimal observation conditions, the number of visible satellites from the four global navigation satellite systems(GNSSs) can rise to approximately 50. This substantially elevates the computational demands for position determination. To expedite position calculations without compromising accuracy, we introduce a rapid satellite selection algorithm that merges the geometric distribution approach with the transformation formula technique. The dynamic environment presents more challenges compared with static positioning, being both intricate and less consistent. To bolster the precision and robustness of kinematic positioning, we present a four-GNSS fusion positioning algorithm grounded in the extended Kalman filter. Experimental results indicate that our proposed methodologies can attain centimeter-level precision and enhance computational efficiency.
Tang Haibo, Wan Bohan, Mao Xuchu
. Multi-System Real-Time Kinematic Positioning Based on Fast Satellite Selection and Improved Kalman Filter[J]. Journal of Shanghai Jiaotong University(Science), 2026
, 31(4)
: 992
-1002
.
DOI: 10.1007/s12204-024-2759-3
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