Active compensation system for high-amplitude magnetic disturbance of unknown frequency based on SERF magnetometer

Periodic high-amplitude magnetic field disturbances in the environment can seriously interfere with the accurate measurement of weak magnetic signals in magnetically shielded devices. Active magnetic field compensation systems (AMC) based on dual-integrated resonance controllers (DIR) can effectively suppress magnetic field disturbances of known frequencies. However, the frequency of magnetic field disturbances in the environment is unknown, and the conventional DIR fails. To address the problem, a frequency-adaptive dual-integral resonance controller (FA-DIR) based on the multiple signal classification algorithm (MUSIC) is proposed in this paper. Firstly, the AMC is modeled and the DIR is analyzed. Subsequently, the implementation process of the MUSIC algorithm is presented and the PI-FA-DIR disturbance suppression method is proposed. The frequency estimation performance of the MUSIC algorithm is simulated and evaluated, and the stability of the AMC is verified. Finally, the efficacy of the proposed PI-FA-DIR in suppressing high-amplitude magnetic field disturbances at unknown frequencies is verified through a magnetically shielded cylinder. The experimental results demonstrate that the proposed PI-FA-DIR can effectively estimate the frequency of high-amplitude magnetic field disturbances and offer a superior disturbance suppression capacity for the AMC.