Data fusion of magnetic coils and Hall sensors using Kalman filtering

Abstract

Considering the broad bandwidth of magnetic coils from lower frequencies up to 10 s – 100 s of kHz and the narrow bandwidth of the Hall sensors from DC to low frequencies of the order of 10 s of Hz, an algorithm based on the Kalman filter combining the signals from both types of sensors to accurately estimate the measured magnetic field in tokamak plasma discharges is proposed. The data fusion algorithm utilizing the Kalman filter is described mathematically and validated using experimental data.