Abstract: [Purposes]To improve the detection of low-amplitude gross errors inglobal navigation satellite system real time kinematic (GNSS RTK) signals,which is limited by the traditional 3σ method,and to address the low sensitivity of empirical mode decomposition (EMD) to regional gross errors,an improved 3σ-EMD algorithm is proposed.[Methods]The algorithm combines experimental and simulated data,utilizing statistical and signal processing techniques to detect and reduce noise in GNSS RTK monitoring signals.It follows a multi-stage strategy: rapid identification and correction of significant gross errors using 3σ,adaptive separation of high-frequency noise via EMD,and residual error optimization through a secondary 3σ process.Applied to dynamic deformation monitoring of Tianjin Haihe Bridge,GNSS-RTK was adopted,and signal denoising was conducted by combining the improved 3σ-EMD method.[Findings]Results show that the improved method achieves a gross error detection rate of 66.7%,outperforming standalone 3σ (59.0%) and EMD (25.6%).The signal to noise ratio is increased to 10.44 dB,an 81.9% improvement over the noisy signal.The algorithm reduced the signal amplitude from 69.70 cm to 34.36 cm,optimized the standard deviation to 6.78 cm,and accurately extracted the bridge's fundamental vibration frequency (0.37 Hz).[Conclusions]The study confirms the robustness of the improved 3σ-EMD algorithm in complex environments,enhancing GNSS RTK signal quality for reliable dynamic deformation monitoring of bridges.

Key words: GNSS RTK, bridge deformation monitoring, gross error detection, empirical mode decomposition (EMD), noise reduction, improved 3σ-EMD