Abstract: 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 differenceof 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.

Key words: Wireless sensor network,Multipath effect,Neural network,Object location,Positioning error