Research On Anchor-free Mobile Targets Localization In Wireless Sensor Networks Based On Unmanned Aerial Vehicle

Mobile targets localization is one of the key technologies in Wireless Sensor Network(WSN).But anchors cannot acquire location in some complex environment,localization algorithm based on known nodes would not achieve satisfying performance.Targets localization in anchor–free WSN has become an important research issue.Recent progress in UAV technology has enabled the development of collaborative localization by UAV and WSN,which has attracted more and more attention.This paper investigates the problem of locating mobile targets based on WSN under such a complex environment.Our work is as follows:(1)Aim to locate targets in anchor-free WSN,this work presents a Multiple Extreme Node Search—Distributed Topology Preserving Maps(MENS-DTPM)algorithm.The algorithm chooses the key nodes in the network as the reference nodes and constructs the virtual coordinate system to generate the topology map of the network through a distributed way.Only by using the connectivity between nodes,the algorithm can contributes to the accurate target localization.Compared with similar algorithms,the MENS-DTPM algorithm can select reference nodes more effectively and reflect the structure of the network better.(2)Under the complex environment,the wireless signal is greatly influenced by environment,which causes the localization error.To alleviate this issue,this work designs a collaborative network system consisting of UAV and WSN based on the network topology,and presents a Mobile Localization based on Conditional Random Field(MLCRF)algorithm.The algorithm uses historical data and UAV's broadcast information to establish localization model,introduces an error factor to correct data containing the noise,and solves the positioning model through Pigeon-Inspired Optimization algorithm,which achieves a precise localization of the mobile target.In addition,the algorithm decreases the computational complexity and reduces transmission energy consumption.Experimental results show that the MLCRF algorithm has higher localization accuracy in a complex environment.When the probability of noise error is 40%,the localization accuracy can reach 2.56 m.Finally,this paper designs and implements the mobile target collaborative localization system consisting of UAV and WSN in complex environment,and realizes experiments in real environment.The final experimental results show that the system can generate network topology map self-adaptively and achieve better localization of moving targets.