DocumentCode
484933
Title
Mobile Target Localization Based on Mean Shift in Wireless Sensor Networks
Author
Luo, Haiyong ; Li, Jintao ; Zhao, Fang ; Lin, Yiming ; Zhu, Zhenmin
Author_Institution
Inst. of Comput. Technol., Chinese Acad. of Sci., Beijing
Volume
1
fYear
2008
fDate
6-8 Oct. 2008
Firstpage
248
Lastpage
253
Abstract
In order to localize the mobile targets in real time and with high accuracy, by employing mean shift algorithm to generate the proposal distribution for the joint particle filter, this paper proposes a novel mobile target localization algorithm, which we called mean shift particle filter. The mean shift particle filter algorithm significantly improves the accuracy of the particle state estimation and reduces the necessary number of samples by using the current observations in sampling procedure to obtain a sample distribution. It also reduces the interference among multiple targets in close proximity by weighting samples according to the virtual hamming distances and interaction potentials. By arranging the state distributions of mobile targets, the proposed scheme can handle the multiple peaks in state estimation of mobile targets and improves the localization accuracy.
Keywords
radio direction-finding; state estimation; target tracking; tracking filters; wireless sensor networks; interference reduction; mean shift algorithm; mean shift particle filter; mobile target localization; particle state estimation; state distribution; virtual hamming distance; wireless sensor network; Distributed computing; Interference; Mobile computing; Particle filters; Particle tracking; Proposals; Sampling methods; State estimation; Target tracking; Wireless sensor networks; mean shift; particle filter; target localization; wireless sensor networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Pervasive Computing and Applications, 2008. ICPCA 2008. Third International Conference on
Conference_Location
Alexandria
Print_ISBN
978-1-4244-2020-9
Electronic_ISBN
978-1-4244-2021-6
Type
conf
DOI
10.1109/ICPCA.2008.4783586
Filename
4783586
Link To Document