胡耀文, 孙俊, 方芳, 邵玉斌, 龙华. 基于BP神经网络的接收信号强度的检测方法[J]. 云南大学学报(自然科学版), 2017, 39(4): 534-538. doi: 10.7540/j.ynu.20160773
引用本文: 胡耀文, 孙俊, 方芳, 邵玉斌, 龙华. 基于BP神经网络的接收信号强度的检测方法[J]. 云南大学学报(自然科学版), 2017, 39(4): 534-538. doi: 10.7540/j.ynu.20160773
HU Yao-wen, SUN Jun, FANG Fang, SHAO Yu-bin, LONG Hua. A new method for signal strength detection based on BP Neural Network[J]. Journal of Yunnan University: Natural Sciences Edition, 2017, 39(4): 534-538. DOI: 10.7540/j.ynu.20160773
Citation: HU Yao-wen, SUN Jun, FANG Fang, SHAO Yu-bin, LONG Hua. A new method for signal strength detection based on BP Neural Network[J]. Journal of Yunnan University: Natural Sciences Edition, 2017, 39(4): 534-538. DOI: 10.7540/j.ynu.20160773

基于BP神经网络的接收信号强度的检测方法

A new method for signal strength detection based on BP Neural Network

  • 摘要: 针对查表法在检测外差式接收机的接收信号强度时,对多维数据建立函数表复杂度高,对系统的非线性部分检测结果不稳定且误差较大的问题,提出了一种基于BP神经网络的接收信号强度的检测方法.通过获取外差式接收机中本振AGC、中频AGC的值和输出音频的均值电压,并将其与输入信号源的已知信号强度建立对应关系,组成训练数据和测试数据,建立基于BP算法的训练网络.通过实验仿真和结果对比证明了该检测方法的有效性,减小了检测误差.

     

    Abstract: Table look-up method used in the Heterodyne Receiver to detecting the received signal strength is unable to establish proper function table of multidimensional data,and the test results are instable,the detect errors are large at nonlinear part of the system.To solve these problems,this paper proposes a new method to establish the training network based on BP algorithm by acquiring the value of local oscillation Automatic Gain Control(AGC),intermediate frequency AGC and the average voltage of the detector output,which can then be used to establish the corresponding relationship with known signal strenth of the input,and these data are used as training data and testing data in the network for training and testing.Simulation and experiment results prove that the proposed method is efficient and can reduce the detection error.

     

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