Particle Swarm Optimization for Magnetometer Calibration With Rotation Axis Fitting Using In-Orbit Data

This article demonstrates the performance of an improved particle swarm optimization (PSO) algorithm with scalar checking and rotation axis fitting objectives using in-orbit data, which is obtained from two CubeSats missions, Aalto-1 ESTCube-1, as well simulation reference. The uses sequential refinement process to combine objectives. improvement addresses some challenges magnetometer calibration when data. First, change in magnetic field vector direction at different points orbit uncorrelated spacecraft itself. Second, uncertainty information used reference, e.g., gyroscope noise. Third, available data set heavily affected by mode spacecraft, imposes limitation needed algorithm. PSO applied on simulated order analyze under tumbling rates noise levels. In ideal condition (varying during measurements sufficient sampling rate relative spin rate), objective can reach ?0.1° correction accuracy.