DocumentCode
2256797
Title
Comparisons of three Kalman filter tracking algorithms in sensor network
Author
Zhu, Yifeng ; Shareef, Ali
Author_Institution
Dept. of Electr. & Comput. Eng., Maine Univ., Orono, ME
fYear
0
fDate
0-0 0
Abstract
This paper compares extended Kalman filters with the P, PV and PVA dynamics models for object tracking in wireless network. Experiments shows that PVA achieves the best and P performs the worst in most cases. In addition, increasing the number of pivots can slightly improve the tracking accuracy
Keywords
Kalman filters; object detection; tracking filters; wireless sensor networks; Kalman filter tracking; P dynamics models; PV dynamics models; PVA dynamics models; extended Kalman filters; object tracking; sensor network; wireless network; Acceleration; Distance measurement; Equations; Intelligent networks; Intrusion detection; Monitoring; State estimation; Target tracking; White noise; Wireless sensor networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Networking, Architecture, and Storages, 2006. IWNAS '06. International Workshop on
Conference_Location
Shenyang
Print_ISBN
0-7695-2651-9
Type
conf
DOI
10.1109/IWNAS.2006.22
Filename
1654533
Link To Document