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Academic Editor:Ana Alejos
College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Received 25 March 2015; Revised 6 June 2015; Accepted 7 June 2015; 16 June 2015
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
1. Introduction
Wireless Sensor Networks (WSNs) are composed of a large number of sensor nodes which can collect, compute, and communicate. The sensor nodes form a multihop and self-configured network by means of wireless communication. Sensor nodes deployed in the monitoring area collect and process the information within the monitoring area and then send the information to the observer [1]. It is important to get the location of the sensor nodes. The information collected without location is always meaningless, so localization becomes a key technology in the Wireless Sensor Network.
Since sensor nodes are randomly deployed in the monitoring area, the manual embedding of location in each node is not feasible in many applications. Nodes often get deployed by aircrafts. Global Positioning System (GPS) receivers can determine their location in the area of deployment, but putting GPS receiver on each node is not feasible due to the increasing cost [2]. Instead, the GPS receiver is only deployed on a small number of sensor nodes and then locates the sensor nodes, which are called anchor nodes. Generally, localization approaches in WSNs locate unknown nodes through the location of anchor nodes.
Currently, localization approaches mainly focus on the 2D plane. Since in practice, the nodes in Wireless Sensor Networks are often deployed in the 3D scenario, for example, deep sea, hill or forest, even sky, and so forth, the localization in a three-dimensional environment is more popular and will lead to further development of localization technology. The three dimensional environment is much more complicated and the computational complexity increases greatly. As a result, it is not appropriate to extend the 2D localization algorithm to a 3D algorithm directly. The research on three-dimensional localization is more realistic and localization algorithms in the three-dimensional space are necessary.
In this paper, an improved 3D localization algorithm and a 3D localization model are proposed to improve positioning accuracy...