Research Of Node Localization Algorithm Based On Bounding Box

Wireless sensor networks (WSN) has used sensor techniques, embedded computations, distributed information processing and wireless communication technique, which can cooperate to complete real-time monitoring, sensing and gathering of object information, and transmit it to the user after information processing. In addition, node localization technology is not only the premise that wireless networks can complete identifying, monitoring, tracking and other applications of object information, but aslo the hot issue in the wireless networks research. This thesis focuses on bounding box algorithm of node localization in WSN.Based on bounding box algorithm in wireless sensor networks, this thesis has studied improvement about node localization in high density of nodes. As to the problem in node localization error, this thesis proposes secondary localization in bounding box algorithm under original bounding box. The algorithm divides the rectangular area dealt by bounding box further into2*2cells, and uses anchor nodes and communication radius estimate their centroid. The algorithm makes the four estimated localization and the localization positioned by bounding box as five estimated localization of unknown node and make sum of the distance between the five estimated localization and the anchor nodes in the radius of the unknown nodes.Compared distance sum of the five estimated localization with that of unknown nodes, the algorithm chooses the estimated node localization which is most close to the unknown nodes as the estimated localization of the unknown nodes, so it can prove the accuracy of the localization. The thesis also analyzes the node localization error of the bounding box localization and secondary localization of the bounding box in the regular and irregular communication model.The thesis combines bounding box algorithm with the advantage of extended kalman filter to improve the accuracy in node localization. It divides into two parts:preliminary node localization and accurate part. The nodes are firstly positioned by bounding box algorithm and then the node localization dealt with bounding box algorithm are considered as the initial data in the extended kalman filter that use neighbor nodes information of the unknown nodes to iterate to get more accurate node localization. The algorithm uses resolved unknown nodes as anchor nodes to iterate to get node localization and it sets a limit that the node localization are accurate enough and then iteration stops. The algorithm can improve the accuracy of the node localization in effect.