Algorithm Research on Direction Finder for GM Counters γ Radiation Source Based on BP Neural Network

To meet the requirement of angle directional measurement for radiation source searching, a γ ray direction finder was designed, which consists of four GM counters and a cross lead shielding structure. The shielding body is 1 cm in thickness and 7 cm in radial width. The angle responses of the direction finder to 0.058-3 MeV single energy photons were simulated with GEANT4, and then used as training samples of the BP neural network algorithm to establish the angle inversion method. The input and output parameter models of neural network training samples were designed, and the angular resolution accuracies of three algorithms were compared. It is shown that the algorithm based on mapping and restructuring the training samples gives the best angle inversion accuracy of ±1.5°, and within ±10° when introducing counting fluctuation. The tests for the direction finder to ¹³⁷Cs radiation source show that its angular deviation is within ±6.25°.