Adaptive BDS RTK Positioning with Azimuth-Integer-Based Elevation Masking for Real-Time Deformation Monitoring in...

Real-time kinematic (RTK) positioning in open-pit mining environments is critically compromised by non-line-of-sight (NLOS) signals and anisotropic multipath effects induced by pit walls, haul roads, and industrial infrastructure. Conventional elevation-dependent stochastic models fail to discriminate between geometrically favorable low-elevation satellites and those subject to directional obstruction, resulting in degraded ambiguity resolution and decimeter-level positioning errors that undermine safety-critical deformation monitoring. This paper presents an adaptive RTK positioning framework utilizing azimuth-integer-based elevation masking to explicitly model site-specific obstruction geometry. The proposed method discretizes the horizontal plane into 360 integer-degree sectors, extracts minimum elevation angles per sector from 24 h line-of-sight (LOS) data, and constructs a smoothed 360°mask profile via moving-window filtering. A virtual elevation-angle transformation is introduced to normalize satellite geometry relative to the local mask, enabling adaptive down-weighting of diffraction-susceptible observations within the stochastic model without requiring multi-day satellite repeat arcs or hardware modifications. The approach was validated using 54 h of BDS data collected at eight monitoring stations within the Wangjialing open-pit mine, China. Implementation of the mask model engendered a selective 8.1% reduction in satellite participation (15.66 to 14.39 satellites) while significantly enhancing observation quality. The ambiguity validation ratio improved by 19.5% (from 9.43 to 11.27 in the experimental project), and the fix success rate increased from 92.4% to 97.2% (exceeding the 95% reliability threshold at all stations). The RMS errors in the east, north, and up directions improved by 34.8% to 65.2%, 28.7% to 77.0%, and 44.8% to 70.8%, respectively, with the most dramatic gains observed at stations subject to severe azimuthal obstruction (e.g., ZDH6 vertical RMS: from 50.7 mm to 14.8 mm). By explicitly modeling anisotropic obstruction geometry through discrete angular sampling, the proposed method achieves sub-centimeter positioning accuracy and robust ambiguity resolution in challenging mining environments without additional hardware or empirical threshold tuning, offering a cost-effective solution for large-scale, real-time deformation monitoring systems.