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A dynamic displacement estimation system is developed by integrating laser Doppler vibromter (LDV) and light detection and ranging (LiDAR). The system includes hardware level integration for simultaneous measurement of two devices and data fusion of two measurement signals based on Kalman filter smoothing algorithms. For hardware integration of two devices, the laser beam directions and the triggering of measurement of LDV and LiDAR are controlled on the level of built-in commands of the devices. The distance data sequentially measured by LiDAR is converted to dynamic displacement of high noise and low sampling rate, and fused with the velocity measured by LDV which has high sampling rate and low noise but accumulated bias error when integrated. Using the Kalman filter based data fusion algorithm, it is able to estimate dynamic displacement in which the drawbacks of two devices are effectively removed. The proposed system is applied to a dynamic loading test on a highway bridge and the performance is verified.
