Attitude determination system of nano-satellite

In recent years, the industry of miniature satellite based on cubesat standard has been growing rapidly. This growing industry has changed the direction of miniature satellite from educational and research purposes to application focused. As most of the implemented applications require target pointing, precise attitude determination is highly crucial to the mission success. There are several established attitude determination methods namely the TRIAD algorithm, QUEST algorithm and Kalman filter. They share a common shortcoming of requiring at least two observer-reference pairs as the input to the algorithm. This has caused an issue for nano-satellite’s attitude determination system as the magnetic field generated by the magnetic torquers corrupt the magnetometer reading while performing momentum dumping. To overcome this problem, a modified extended Kalman filter algorithm has been developed in this thesis such that it can work even with the presence of only a single observer-reference pair by trading off attitude knowledge accuracy. From the study, it was noticed that the accuracy of the attitude knowledge drops drastically with time when utilizing only a single observer-reference pair. To further improve the performance, an alternative approach has been developed such that the attitude knowledge accuracy can be retained even when magnetic torquers are switched on. The alternative approach used a hybrid optimization method based on particle swarm optimization and iterated extended Kalman filter to calibrate the magnetometer in-orbit. Beside calibrates for the coupling effects of magnetic torquers, the proposed magnetometer calibration method also calibrates for the in-orbit variation that affects the measurement accuracy of the magnetometer. Both simulation and experimental results show that the measurement accuracy of magnetometer is enhanced and the problem of magnetometer reading corruption while performing momentum dumping is resolved. MEMS based gyroscope is typically used in a nano-satellite. Its drawback is the low accuracy. While there are studies to improve the performance of MEMS based gyroscope, they either require an array of MEMS gyroscopes or a high complexity algorithm and thus not suitable for nano-satellite applications. To address this issue, a low complexity Kalman filter for MEMS based gyroscope has been introduced in this thesis. Besides having a lower computational load, it also reduces the MEMS based gyroscope noise in all three-axes without the implementation of extra gyroscopes.Master of Engineerin