Three-Axis Attitude Estimation Of Satellite Through Only Two-Axis Magnetometer Observations Using LKF Algorithm

Estimation of satellite three-axis attitude using only one sensor data presents an interesting estimation problem. A flexible and mathematically effective filter for solving the satellite three-axis attitude estimation problem using two-axis magnetometer would be a challenging option for space missions which are suffering from other attitude sensors failure. Mostly, magnetometers are employed with other attitude sensors to resolve attitude estimation. However, by designing a computationally efficient discrete Kalman filter, full attitude estimation can profit by only two-axis magnetometer observations. The method suggested solves the problem of satellite attitude estimation using linear Kalman filter (LKF). Firstly, all models are generated and then the designed scenario is developed and evaluated with simulation results. The filter can achieve 10e-3 degree attitude accuracy or better on all three axes.