Abstract
In this study, the extended Kalman filter was firstly explicated on the basis of quaternion. In order for the attitude estimation to be improved, multiplicative quaternion-based Kalman filter was presented. This filter helps to increase the convergence, and decrease sensitivity to the primitive conditions. In this research, inertia and reference sensors have been utilised for attitude estimation. Also, modelling and simulation of quaternion-based attitude estimation is initially performed and partially verified. Subsequently, an approximate statistical method was utilised to evaluate filter convergence. According to the simulation result, attitude and bias gyroscope fall in a safe region. Finally, a Mont Carlo simulation was also performed. The comparison and verification of statistical results indicated a small and acceptable deviation between the two approaches, thus, it can be concluded that the simpler approximate statistical approach is also valid for elevation filter convergence and can provide valuable knowledge needed in the filter design.
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