Observation-Domain Multipath Mitigation in Global Navigation Satellite System Positioning Using Multi-Baseline Stacked Carrier-Phase Residuals

Multipath noise, a site-specific error influenced by the surrounding environment of Global Navigation Satellite System (GNSS) antennas, continues to be a significant challenge in kinematic GNSS positioning, particularly for detecting subtle crustal deformations over hours to days. While the sidereal filter is widely used for its simplicity, it is not always well-suited for multi-GNSS data. The Multipath Hemispherical Map (MHM) method offers better performance and multi-GNSS compatibility. Still, it is often implemented in a software-dependent manner, and isolating multipath from other errors, such as tropospheric delays, is difficult. To overcome these issues, we propose the Multi-Site Stacked MHM (MSS-MHM) method, which builds a hemispherical map by stacking carrier-phase residuals from multiple short-baseline relative positioning solutions. In this setup, residuals that substantially reduce common-mode tropospheric, ionospheric, and clock errors are mapped onto a satellite azimuth-elevation grid. This map is then used to correct the original Receiver Independent Exchange Format (RINEX) observation file, thereby enabling use with a wide range of software. Applying MSS-MHM to 30-second long-baseline kinematic analyses with multi-GNSS data showed that increasing both the number of baselines and stacking days significantly reduced coordinate time series noise. Power spectral density analysis indicated that noise reduction was most effective for periods longer than ~1,000 seconds. Moreover, using the corrected RINEX file across four different positioning software packages (Double-Difference and Precise Point Positioning strategies) improved coordinate stability in our tests. These results highlight MSS-MHM as a software-agnostic, observation-level correction framework for multipath mitigation, applicable across the strategies and software evaluated here.

 

Acknowledgments: The SoftBank's GNSS observation data used in this study was provided by SoftBank Corp. and ALES Corp. through the framework of the "Consortium to utilize the SoftBank original reference sites for Earth and Space Science."