Wireless Sensor Network Localization Algorithm With Constrained Events

As a developing technology,people are paying more and more attention to wireless sensor network.In recent years,it is changing our lives and is listed as one technology of 21 century.It is benefited from its good prospects,including smart home,road traffic monitoring,forest fire prevention and so on.In the application,the node position information is extremely important,the activities need to monitor the position information of nodes to determine the location of these events.So It is meaningless if we don't know the position of nodes.Recently,one new localization technology with uncontrolled events is depended on the original event-driven.To some extent,it liberated the event transmitting equipment,a large number of random events and high-density nodes give algorithm high accuracy.It also can improve the positioning efficiency.But the practical application of this algorithm still has some limitations,because the scanning of each event is required to cover all the nodes.But the algorithm still has some constraints,so the LCSLE(Sensor node Localization with Constrained Straight-line Scan Events)is proposed in the following,which completely liberated the event launch equipment.It is based on DLSE(Sensor Node Driven Localization With Straight-line Scan Events).In LCSLE algorithm,the following proposed DONS(Difference of node Sequence)and finally established the optimal effective sequence set by optimizing the sequence of nodes continuously.It reduces the computation complexity of the algorithm DLSE and improves the localization efficiency.In addition,the original algorithm can not satisfy the requirement of positioning accuracy.So we propose the algorithm AELA(an asymmetric event-driven localization algorithm),which is depended on LWPE(Sensor Node Localization With Wave Propagation Events)in chapter 4.The core idea of AELA is curvature,two events transmitters and two anchor nodes are arranged in constrained space.Then we discuss the localization methods in three cases.We finally perform experiments in the indoor corridors,and the results show that AELA has high performances on localization accuracy and the algorithm is very stable.