Additive Multi-rate Delayed Extended Kalman Filter Attitude Estimation Fusing Gyroscope and Star Tracker Sensors

In this paper, information of gyroscope and star tracker attitude sensors are fused for attitude estimation in the presence multi-rate sensors and the star tracker measurement delay. To this end, the extended Kalman filter (EKF) is modified to reduce the computation burden avoiding computation repetitions after arrival of the delayed multi-rate measurements. The algorithm is modified such that it is truly estimating the attitude in the absence of the star tracker measurements due to low sampling rate frequency and the estimation is optimized after its arrival. Toward this, the idea of predicting the measurement model, firstly proposed in [7], is employed and extended for the EKD based attitude estimation in the presence of multi-rate gyroscope and star tracker sensory information and delay in the star tracker measurement is also involved in the proposed method. The efficiency of the proposed method is finally demonstrated through both simulation and experimental data.