On-Orbit Magnetometer Data Calibration Using Genetic Algorithm and Interchangeability of the Calibration Parameters

Abstract

Magnetometers are important sensors with applications in the attitude determination and control systems of satellites. CubeSats have certain limitations related to power, mass, and volume. Due to this, CubeSat magnetometers are not separated from other electrical circuits inside the satellite. Thus, it is important to calibrate the magnetometer, simulating operating conditions while the satellite is running before the launch. However, due to the limited facilities, not every CubeSat is able to calibrate its magnetometers properly on the ground. This study focuses on the calibration of on-orbit magnetometer data observed by BIRDS-3 CubeSats with a genetic algorithm. High oscillations in the total magnetic field were found in the on-orbit magnetic field data measured by magnetometers inside BIRDS-3 CubeSats. Nine unknowns, scaling factors, non-orthogonal angles, and offsets are identified with the genetic algorithm. This paper discusses the factors that affect the high oscillations in the measured total magnetic field data. For the calibration, we used magnetic field data similar to those of a model magnetic field, as the deviation is smaller. This paper presents the accuracy of determining unknowns using the genetic algorithm, as well as the interchangeability of the answers with additional orbit data from the same satellite. This method can be used in the future to calibrate magnetometers inside CubeSats before or after launch.