Dynamic displacement estimation and modal analysis of long-span bridges integrating multi-GNSS and acceleration measurements

Abstract Compared with acceleration-based modal analysis, displacement can provide a more reliable and robust identification result for output-only analysis of long-span bridges. However, the estimated displacements from acceleration records are frequently unavailable due to unrealistic drifts. Aiming at obtaining accurate stable results determining parameters, this study develops multi-rate weighted data fusion approach estimating responses in dynamic monitoring structures based on global navigation satellite system (GNSS) measurements. The initially derives local estimations sensors via Kalman filter algorithm colored measurement noise, later uses criterion scalar linear minimum variance fuse estimations. Then, structural pamameters identified by employing data-driven stochastic subspace (SSI) algorithm. proposed is validated four degree-of-freedom numerical model then applied bridge engineering practice. illustrate that reduce error GNSS-obtained expand recognizable frequency range introducing component measurement.