Multi-rate Kalman filtering for the data fusion of displacement and acceleration response measurement in dynamic system monitoring

By Andrew W. Smyth, Meiliang Wu. 2007

373 citations recorded by the source corpus.

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Wireless displacement sensing system for bridges using multi-sensor fusion (2014, methodology): “Efforts have been made to compensate for the low-frequency displacement component of the displacement from acceleration by combining displacement from devices such as GPS and LDVT, but the methods are limited in full-scale application due to issues of accuracy and difficulty of sensor installation [”
A dual Kalman filter approach for state estimation via output-only acceleration measurements (2015, background): “Smyth and Wu [9] proposed a multi-rate Kalman filter for the online fusion of measured displacement and acceleration data sampled at different rates.”
Reference‐free structural dynamic displacement estimation method (2018, methodology): “To overcome this limitation, several researchers have applied Kalman filtering to simultaneously remove noise from recorded acceleration records of one or multiple points and predict displacements.(1,15,16) These approaches assume a model for the error that is not necessarily true for general sensor”