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Communication Dans Un Congrès Année : 2023

Minimization of Parameter Sensitivity to Pre-Estimation Errors and its Application to the Calibration of Magnetometer Arrays

Minimisation de la sensibilité des paramètres par rapport à des erreurs de pré-estimation et son application à la calibration d'un réseau de magnétomètres

Résumé

We consider the problem of parameters estimation in the situation where a subset of parameters of the underlying model has already been estimated. Potential errors in the pre-estimated parameters limit the accuracy in the computation of the still unknown parameters in a way that crucially depends on the symmetries of the data set. In this article, we develop an optimization approach that minimizes the sensitivity to errors in the determination of parameters by determining optimal weights that depend on both the model and the input data in the situation where the data are incomplete. We apply the method to the problem of calibrating the sensor positions in an array of magnetometers whose scale factors and biases have been estimated beforehand.
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hal-04072014 , version 1 (17-04-2023)

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Raphaël Neymann, Hendrik Meier, Hugo Lhachemi, Christophe Prieur, Antoine Girard. Minimization of Parameter Sensitivity to Pre-Estimation Errors and its Application to the Calibration of Magnetometer Arrays. ECC 2023 - 21st European Control Conference, Jun 2023, Bucarest, Romania. ⟨10.23919/ECC57647.2023.10178334⟩. ⟨hal-04072014⟩
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