As the constellation satellite market is growing, there is a need to develop high precision fluxgate magnetometers. To start with this task, we want to be able to characterize some different types of magnetic noise that typical spacecraft might need to deal with. We measure the magnetic fields of simple dipoles, oscillating magnetic sources such as electric motors, and current carrying wires. If we know the magnetic fields of typical noise sources, then machine learning algorithms can be trained to filter out these signals. Therefore the only thing remaining in our data will be the geophysical signal that we want to measure. After creating and refining this method, we will not have to exert as much effort trying to create miniature, magnetically clean magnetometers and spacecraft.