Sensing devices are the main support for any experimental activity. The user expects that they are transparent, i.e., any measurement provides an assessment of a physical variable. Recent microelectronics developments caused significant modifications in the products offered by the market. Data fusion is the source of a recent jump in that technology, but the transparency of the result is no longer evident. In this paper, the authors consider the data fusion of displacement and acceleration measurements via a Kalman filter. The assemblage of two sensors is produced from scratch, and the critical aspects of the consequent data fusion are emphasized.
Validation range for KF data fusion devices
Casciati, F.
;Vece, M.
2018-01-01
Abstract
Sensing devices are the main support for any experimental activity. The user expects that they are transparent, i.e., any measurement provides an assessment of a physical variable. Recent microelectronics developments caused significant modifications in the products offered by the market. Data fusion is the source of a recent jump in that technology, but the transparency of the result is no longer evident. In this paper, the authors consider the data fusion of displacement and acceleration measurements via a Kalman filter. The assemblage of two sensors is produced from scratch, and the critical aspects of the consequent data fusion are emphasized.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
