Adaptive filter entropy monitoring method for scalar magnetic detection using optically pumped magnetometers

Abstract

Abstract In this paper, an adaptive filtering minimum entropy detector (AF-MED) method is proposed, which is an improvement on the minimum entropy detector (MED) method. The improvement can be divided into two parts. Firstly, in view of the low detection rate of the MED method in the case of low signal-to-noise ratio (SNR), an adaptive filtering technology is added, which can accurately and dynamically determine the frequency range of the magnetic field according to the moving speed of the magnetic target, and effectively restrain the influence of environmental noise on the magnetic field. Compared with the MED method, the detection rate is increased by 48%. Secondly, using the kernel density estimation method to calculate the probability density value, the advantage is that there is no need to make any predictions or assumptions about the target, which makes the method more convenient to achieve. Furthermore, in this study, numerous simulations and experiments were performed, and the cell averaging constant false alarm rate detector was used to calculate the detection rate. The average value of detection rates of AF-MED, MED and the orthogonal basis function (OBF) are about 69%, 21% and 43% respectively when SNR is low (SNR from −25 dB to −50 dB). The results demonstrated the superiority of the proposed method over the MED and the OBF.