费扬, 杜庆治. 基于BP神经网络模型的RSSI测距方法研究[J]. 电波科学学报, 2018, 33(2): 195-201. doi: 10.13443/j.cjors.2017073001
      引用本文: 费扬, 杜庆治. 基于BP神经网络模型的RSSI测距方法研究[J]. 电波科学学报, 2018, 33(2): 195-201. doi: 10.13443/j.cjors.2017073001
      FEI Yang, DU Qingzhi. RSSI ranging method based on BP neural network model[J]. CHINESE JOURNAL OF RADIO SCIENCE, 2018, 33(2): 195-201. doi: 10.13443/j.cjors.2017073001
      Citation: FEI Yang, DU Qingzhi. RSSI ranging method based on BP neural network model[J]. CHINESE JOURNAL OF RADIO SCIENCE, 2018, 33(2): 195-201. doi: 10.13443/j.cjors.2017073001

      基于BP神经网络模型的RSSI测距方法研究

      RSSI ranging method based on BP neural network model

      • 摘要: 针对传统信号传播路径损耗模型接收的信号强度指示(received signal strength indication, RSSI)测距误差较大, 提出了基于反向传播(back propagation, BP)神经网络模型的RSSI测距方法.首先, 研究分析传统信号传播路径损耗模型及测距误差; 其次, 利用BP神经网络构建新的路径损耗模型, 并将该模型应用到RSSI测距中, 对基于BP神经网络模型的RSSI测距方法进行研究; 最后, 通过实验和MATLAB仿真对测距方法进行验证.仿真结果表明:BP神经网络模型的RSSI测距误差比传统信号传播路径损耗模型的RSSI测距误差要小.

         

        Abstract: In order to solve the problem of signal propagation path loss model and reduce the error of received signal strength indication(RSSI) distance measurement, we propose a RSSI ranging method based on back propagation(BP) neural network model. Firstly, we research and analyze the error model and the traditional ranging signal propagation path loss. Secondly, using BP neural network, we propose a new path loss model, which is applied to RSSI ranging, and then carry out research on RSSI location method based on BP neural network model. Finally, the method of distance measurement is verified by experiment and MATLAB simulation. The simulation results show that the RSSI ranging error of the BP neural network model is smaller than that of the traditional signal propagation path loss model RSSI.

         

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