一种电磁频谱信号检测智能化门限设计方法OA

In view of the problems existing in the traditional signal detection threshold-setting methods in complex electromagnetic environments,such as difficult threshold setting,poor adaptability,high false-alarm/miss-detection rates,and great difficulty in weak signal detection,an intelligent threshold design method for electromagnetic spectrum signal detection is proposed.A decision-making intelligent agent is constructed using deep reinforcement learning to achieve autonomous cognition of one-dimensional electromagnetic spectra.It can intelligently provide adaptive signal detection threshold values in a segmented manner,achieving a signal detection rate of 91.9%and a 1.8%increase in the detection rate of weak signals(signal-to-noise ratio≤5 dB).The technology can automatically enable front-end detection equipment to autonomously detect electromagnetic signals without human intervention throughout the process.It has been tested in practical projects of unmanned autonomous signal detection,and all indicators meet the requirements of practical engineering applications.