A New Method for Reduction of Atomic Magnetometer Noise Based on Multigene Genetic Programming
Wei Quan, Feng Liu, Wenfeng Fan
An ultra-high precision magnetic field measurement is of great scientific and economic significance. An atomic magnetometer that operates in a spin-exchange relaxation-free (SERF) regime has superior sensitivity and, thus, is of great significance for the ultra-high precision magnetic field measurement. In order to reduce the noise of a SERF atomic magnetometer and further improve its sensitivity, a method for noise reduction based on the multigene genetic programming (MGGP) is presented. Different from the existing methods, in this method, the model of magnetometer noise is established based on the experimental data. Namely, the noise of the SERF atomic magnetometer is first modeled by the MGGP algorithm and then reduced by the obtained model. Besides, in this way, the sensitivity is improved. The experimental results indicate that our MGGP model can adequately reflect the characteristics of the SERF magnetometer noise. Moreover, after applying the proposed method, the sensitivity of the SERF magnetometer is improved about 13 times at 1 Hz, and there is also a significant sensitivity increase at the frequencies less than 10 Hz. Therefore, the proposed method can effectively reduce the noise and improve the sensitivity of the SERF magnetometer in the low-frequency band.
IEEE Access•Jan 1, 2019•3 citations