Today's most accurate measurements of the gravitational acceleration are based on interferometric reconstruction of the vertical trajectory followed by a test body launched in a vacuum chamber. The gravity value g is one of the parameters of a model function derived from the law of motion of the body, and is estimated by a least squares adjustment. In this paper we present the regression analysis applied to the IMGC-02 absolute gravimeter and the associated uncertainty propagation We also show how a suitable choice of the reference height z, at which g is calculated, can yield a minimum-variance estimate. This choice is based on the covariance matrix of the parameter estimates provided by the adjustment algorithm.
Uncertainty Propagation in a Non-linear Regression Analysis: Application to a Ballistic Absolute Gravimeter (IMGC-02) / Bich, Walter; D'Agostino, Giancarlo; Germak, ALESSANDRO FRANCO LIDIA; Pennecchi, FRANCESCA ROMANA. - (2007), pp. 4362566.30-4362566.34. (Intervento presentato al convegno AMUEM 2007 - IEEE Internat. Workshop on Advanced Methods for Uncertainty Estimation in Measurement tenutosi a Sardagna (TN), Italy nel 16-18 July 2007) [10.1109/AMUEM.2007.4362566].
Uncertainty Propagation in a Non-linear Regression Analysis: Application to a Ballistic Absolute Gravimeter (IMGC-02)
BICH, WALTER;D'AGOSTINO, GIANCARLO;GERMAK, ALESSANDRO FRANCO LIDIA;PENNECCHI, FRANCESCA ROMANA
2007
Abstract
Today's most accurate measurements of the gravitational acceleration are based on interferometric reconstruction of the vertical trajectory followed by a test body launched in a vacuum chamber. The gravity value g is one of the parameters of a model function derived from the law of motion of the body, and is estimated by a least squares adjustment. In this paper we present the regression analysis applied to the IMGC-02 absolute gravimeter and the associated uncertainty propagation We also show how a suitable choice of the reference height z, at which g is calculated, can yield a minimum-variance estimate. This choice is based on the covariance matrix of the parameter estimates provided by the adjustment algorithm.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
