Multiplicative Error State Kalman Filter vs Nonlinear Complimentary Filter for a High Performance Aircraft Attitude Estimation

Abstract

Modern control law designs increasingly use aircraft attitude information to improve aircraft manoeuverability. Attitude information allows for gravity term compensations in the longitudinal as well as lateral directional control laws of a typical fighter aircraft. Methodologies and comparisons of multiplicative error state Kalman filter (MEKF) and nonlinear complimentary filter for estimation of attitudes of a high performance aircraft using its onboard autonomous sensors is presented. Shows a problem in pitch angle estimation beyond ± 80 deg in the MEKF and a solution is proposed for the same for the first time. Also presents novel aiding sensor modelling for the implementation of attitude heading reference system for this class of aircraft for the first time. The filter formulations are evaluated using full range manuoevering real flight test data.