Three Dimensional Attitude Estimation via the Triad Algorithm and a Time-varying Complementary Filter

An innovative implementation of attitude estimation in 3 degrees of freedom (3-DOF) combining the TRIAD algorithm [1] and a time-varying nonlinear complementary filter (TVCF) is derived. This work is inspired by the good performance of the TVCF in 1-DOF [2] developed for applications limited to small mobile platforms with low computational power. To demonstrate robust 3-DOF estimation, information from vector and rate-gyroscope measurements are fused. Simulation and experimental results demonstrate comparable performance to the extended Kalman filter (EKF) and improved performance over alternative methods such as sole gyroscope rate-integration and the TRIAD algorithm without the TVCF as a pre-filter.