A Burst Signal Detection Method Based on Probabilistic Spectral Intensity Matrix Strain Features
Dingkun Ma, Tong Jiang, Zongjie Ding, Yan Ma, Yi Ding, Sujun Wang, Yifan Ping · 2024
Burst signals have recently become a critical factor in radiation source processing, and the action of detecting and capturing is one of the most important factors in resolving this issue. The article proposes an innovative method of burst signal detection with a probabilistic spectral intensity matrix, which accumulates the probabilistic features of the signal for some time. Strain features corresponding with burst signal can be extracted to capture the desired signal. The proposed method provides a novel way to solve the problems of burst signal detection and has an excellent success rate. Experiment results show the effectiveness of the method in burst signal stable capture, offering significant value and bright prospects for resolving the growing burst signal detection in the radiation source processing field.