Extended Kalman Filter-based Attitude Estimation using Magnetometer- and Sun Sensor-Aided MEMS Gyros

A novel idea is being proposed to reuse the spent upper stages of launch vehicles to conduct micro-gravity experiments. The spent stages, which remain in orbit, acts as a small spacecraft with limited power and space to meet the requirements. In order to achieve the mission objectives, attitude of the spacecraft must be determined. A new system comprising of rate class micro-electro-mechanical system (MEMS) gyroscopes, three-axis magnetometers, and Sun sensors is to be used. The paper focuses on the design of an attitude estimation algorithm using the MEMS gyros as the primary sensor. Secondary sensors are to be used to aid the gyro measurements. Algorithm using inertial navigation system (INS) error state-based extended Kalman filter (EKF) is studied in this work. The paper includes detailed derivation of the algorithm and reference models for the secondary sensors. Performance of the algorithm during magnetometer failure and eclipse is also quantified.