摘要
无线电信号在传播过程中,由于复杂的环境和外界噪声导致信号接收的不确定性。为有效增强检测的特征频率,减少干扰频率成分,更清晰地识别目标频率特征,将周期势系统势阱模型与Gaussian Potential(GP)势阱模型相结合提出GP-周期势随机共振系统,令待测信号、噪声及随机共振系统产生最佳的共振效果,对无线电弱信号进行检测,并与传统随机共振系统和周期势随机共振系统检测无线电弱信号的效果进行对比。实验结果表明,GP-周期势随机共振系统在无线电弱信号检测中识别目标频率更清晰,频谱更平坦,和传统随机共振系统相比对噪声的利用率更高。
In the process of radio signal propagation,the uncertainty of signal reception was caused by complex environment and external noise.In order to better enhance the characteristic frequency of detection,reduce the interference frequency component,and clearly recognize the target frequency characteristics,the periodic potential well model was combined with the Gaussian Potential(GP)well model to propose a stochastic resonance system based on GP-periodic potential.The measured signal,noise and stochastic resonance system produced optimal resonant effect to detect radio weak signal,and the detection effect was compared with that of the traditional and periodic potential stochastic resonance systems.The simulation experiment results demonstrate that the GP-periodic potential stochastic resonance system recognizes the target frequency in the signal detection more clearly and the spectrum is flatter.The utilization of noise is higher than that of the traditional stochastic resonance system.
作者
杜太行
陈霞
孙曙光
郝静
王锐雄
梁杰
DU Tai-hang;CHEN Xia;SUN Shu-guang;HAO Jing;WANG Rui-xiong;LIANG Jie(School of Artificial Intelligence,Hebei University of Technology,Tianjin 300130,China;School of Information Technology,Hebei University of Economics and Business,Shijiazhuang 050000,China;School of Automation and Communication Engineering,Hebei University of Water Resources and Electric Engineering,Cangzhou 061000,China)
出处
《仪表技术与传感器》
CSCD
北大核心
2020年第7期100-104,共5页
Instrument Technique and Sensor
基金
河北省教育厅资助科研项目(ZD2016108)。
