Predictive filtering for attitude estimation without rate sensors

In this paper, a real-time predictive filter is derived for spacecraft attitude estimation without the utilization of angular rate measurements from gyros. The formulation described in this paper is shown using only attitude sensors (e.g., three-axis magnetometers, sun sensors, star trackers, etc.). The new real-time nonlinear filter predicts the required torque modeling error input in order to propagate the spacecraft dynamic model, so that model responses match the measured vector observations. Algorithms are developed which require the output estimates to track either the body measurements from the on-board sensors or the inertial reference trajectories generated from ephemeris data sets. The real-time predictive filter is used to estimate the attitude of the Solar, Anomalous, Magnetospheric Particle Explorer (SAMPEX) spacecraft. Results using this new algorithm indicate that the real-time predictive filter accurately estimates the attitude of an actual spacecraft with the sole use of magnetometer sensor measurements.