ROBUST AVIONICS DEAD RECKONING FILTERING SCHEME VIA LMI

摘要

A new application of a Kalman-like robust filtering scheme to Avionics Dead Reckoning is presented. Inertial and air data measurements are used in order to reconstruct the attitude and the body frame velocity of a general aviation aircraft. The proposed estimation algorithm is based on an affine representation of the non linear model of the system, leading to a Kalman filter gain optimizing procedure under a set of Linear Matrix Inequality constraints. The resulting procedure fulfills the standard accuracy requirements for large set of flight condition, and exhibits better robustness characteristics with respect to the model uncertainty than the classic and widely used Extended Kalman Filter.