Dynamic Displacement Estimation Using Data Fusion
Vibroengineering PROCEDIA 2017
Sabīne Upnere, Normunds Jēkabsons

The paper describes a Kalman filtering technique for dynamic displacement estimation using accelerometer and laser sensor measurements. Data fusion of measurements from multiple sensors can give the more accurate results because of different advantages of sensors. Since the acceleration and displacement have different sampling rates, the multi-rate Kalman filter is applied. The filter is expanded with the fixed interval smoother to improve reconstruction accuracy of displacements. A modelled signal consisting of two sinus functions and Gaussian distributed noise is used to validate developed state-space model.

Atslēgas vārdi
Kalman filter, smoother, accelerometer sensor, laser sensors, sensor data fusion

Upnere, S., Jēkabsons, N. Dynamic Displacement Estimation Using Data Fusion. Vibroengineering PROCEDIA, 2017, Vol. 15, 145.-149.lpp. ISSN 2345-0533. Pieejams: doi:10.21595/vp.2017.19425

Publikācijas valoda
English (en)
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