Multipath Effects Mitigation in Offshore Construction Platform GNSS-RTK Displacement Monitoring Using Parametric Temporal Convolution Network

The Global Navigation Satellite System (GNSS), renowned for its high precision and automation, has shone brightly in the deformation monitoring of offshore facilities and sea-crossing bridges. However, antennas placed in these locations are often subject to signal interference from various reflective surfaces, such as rivers and oceans, which significantly compromises observation accuracy and reliability. Synthesizing previous research, we first propose a method for multipath dataset construction, which involves GNSS observation linear combinations, detailed mapping of the near-field reflector, and employed static solution residuals as reference. Subsequently, we construct and train a corresponding para-TCN (parametric Temporal Convolution Network) to enable real-time prediction of multipath prediction. Through time domain and frequency domain analysis, it has been demonstrated that the trained network can capture the main features of multipath models and suppress those components in both the data distribution and frequency band, effectively mitigating the interference of multipath errors in observations.