Title :
SVM-based target tracking in combined with Sensor Scheduling
Author :
Liqun Shan ; Wang, Jinkuan ; Zhigang Liu ; Du, Ruiyan
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
A new target tracking method is presented to improve target location accuracy in the case of prolonging the network lifetime. The presented method utilizes sensor scheduling to extend the network lifetime and support vector machine for target tracking. Analysis and simulation results show that the algorithm has a high target localization accuracy by comparing with the least-square location method.
Keywords :
least squares approximations; scheduling; support vector machines; target tracking; wireless sensor networks; SVM-based target tracking; improve target location accuracy; least-square location method; network lifetime; sensor scheduling; support vector machine; Batteries; Broadcasting; Computer networks; Intelligent sensors; Scheduling; Sleep; Support vector machine classification; Support vector machines; Target tracking; Wireless sensor networks; classification; sensor scheduling; support vector machine (SVM); target tracking;
Conference_Titel :
Computer Design and Applications (ICCDA), 2010 International Conference on
Conference_Location :
Qinhuangdao
Print_ISBN :
978-1-4244-7164-5
Electronic_ISBN :
978-1-4244-7164-5
DOI :
10.1109/ICCDA.2010.5541272
