【摘要】 在研究分析室内无线信号传播特性和传统的室内定位算法的基础上,提出了用BP神经网络来拟合室内无线信号传播模型,避免了对无线信号传播模型中参数A和n的不精确估计.在训练完成的BP神经网络的输入层输入接收信号强度值RSSI(Received Signal Strength Indicator),在输出层即可得到对应的距离值,再利用泰勒级数展开法确定盲节点的坐标位置.最终通过Matlab仿真和ZigBee平台实验验证了算法的可行性和有效性.更多还原

【Abstract】 Based on lots of research and analysis on indoor radio signal propagation features and the traditional indoor location algorithms,a new method that uses BP(Back Propagation) neural network to fit the indoor radio signal propagation model is proposed,which avoids inaccurately estimating the parameters A and n in the indoor radio signal propagation model.Distance value proportional to the RSSI(Received Signal Strength Indicator) input through the well-trained BP neural network is obtained,and then Taylor series expansion algorithm is used to determine the coordinates of the blind node.Finally,the simulation and experiment results on the ZigBee platform verify the feasibility and effectiveness of the proposed algorithm.更多还原