Survey of nonlinear attitude estimation methods

The processes of attitude estimation, involving estimation of a vehicle's orientation from body measurements and filtering of noisy measurements is presented. Another way is to use the kinematics model propagated with three axis rate integrating gyros, the rates measured by gyros drift over time. Therefore, to determine the drift, the altitude state vector is supplemented by three or more states. The multiple extended Kalman filter is a simple and flexible tool for a variety of measurements, increasing powerful processors promote increased spacecraft autonomy. The orthogonal altitude filters are nonlinear filters and the predictive filter is used for point-by-point estimation. These filters require the probability density function to be Gaussian and creative ways are used to increase in the computation power to be useful for the future spacecraft applications.