A globally asymptotic attitude estimation using complementary filtering

We propose a simple and efficient globally asymptotic attitude estimation solution in which complementary linear filters are combined with TRIAD algorithm. The solution leads to many possible combinations between the form of the filter (direct or passive) and its order. Lyapunov analysis results for the proposed direct and passive second order filters are addressed. Global asymptotic convergence of the filtered signals has been shown. The proposed solution includes the estimation of bias of gyro-rate and the possibility of improving the quality of the estimation by increasing the order of the filter. The performance of the filters and the AHRS solutions are demonstrated via many simulations.