作　　者： (闫俊伢）; (钱宇华）; (李华锋）; (马尚才）;

机构地区： 山西大学商务学院信息学院,太原030031

出　　处： 《计算机科学》 2017年第8期71-75,共5页

摘　　要： 为了实现802.15.4a无线传感器网络中的目标定位,提出了一种新的基于多径距离和神经网络的目标定位检测算法。首先通过目标出现时对多径效应的影响估计出到达时间差,从而计算出通信传感器节点之间的多径距离;然后把多径距离作为神经网络的输入,并将目标位置用于神经网络的训练;最后通过选择多径距离估计值和测量值的差的最小成本组函数来定位目标位置。对单目标和多目标的定位检测仿真结果表明,即使当网络中传感器数量和目标增加时,所提出的定位算法的误差累积分布函数也不会增大,而且其定位误差比其他定位算法的误差小,从而增强了网络的鲁棒性,提高了网络中传感器承受故障的能力。 In order to realize the object location in 802.15.4a wireless sensor networks,a new algorithm for object location and detection based on multipath distance and neural network was proposed in this paper.Firstly,the time difference of arrival time is estimated when the presence of the object causes disturbances in the multipath effect,and the multipath distance between the nodes of the communication sensor is calculated.Then the multipath distance is used as the input of the neural network,and the object location is used for neural network training.Finally,minimum cost group function of the difference between the multipath distance estimation and its measurement is chosen to locate the object position.The simulation results of the localization and detection for single object and multiple objects show that the cumulative distribution function of error does not increase and the positioning error is smaller compared to other localization algorithms using the positioning algorithm proposed in this paper even when the quantity of sensors and objects in the network increases,thereby the robustness of the network is enhanced and the ability of network sensor to withstand failure is improved.

关 键 词： 无线传感器网络 多径效应 神经网络 目标定位 定位误差