An improved location algorithm in Wireless Sensor Network

Author(s):  
Jinlong Liu ◽  
Zhilu Wu ◽  
Zhendong Yin
2017 ◽  
Vol 13 (07) ◽  
pp. 57
Author(s):  
Min Wang

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">For exploring wireless sensor network - a self-organized network, a new node location algorithm based on statistical uncorrelated vector (SUV) model, namely SUV location algorithm, is proposed. The algorithm, by translating the node coordinate, simplifies the solution to double center coordinate matrix, and gets the coordinate inner product matrix; then it uses statistical uncorrelated vectors to reconstruct the coordinates of the inner product matrix and remove the correlation of inner matrix of coordinates caused by the ranging error, so as to reduce the impact of ranging error on subsequent positioning accuracy. The experimental results show that the proposed algorithm does not consider the network traffic, bust still has good performance in localization. At last, it is concluded that reducing the amount of communication of sensor nodes is beneficial to prolong the service life of the sensor nodes, thus increasing the lifetime of the whole network.</span>


2013 ◽  
Vol 373-375 ◽  
pp. 367-372
Author(s):  
Yun Zhou Zhang ◽  
Dong Fei Wei ◽  
Ze Yu Wang

In this paper, we propose a wireless sensor network self-location improved algorithm based on the Unmanned Aerial Vehicle (UAV). The path and the signal emission mechanism of the UAV are rational planning. The k-3 covering method is used to programming the working point and the path of UAV. We also set up a wireless sensor network localization experiment platform based on the UAV and then we carry on several experimentations and curve fitting on the surface-to-surface and surface-to-air distance curve. Experimental results show that the self-location system built based on the theories this paper proposed has an air-to-surface actual distance error of 4.42m and the algorithms positioning error is 3.67m which has very high work efficiency.


Sign in / Sign up

Export Citation Format

Share Document