Title :
Decentralized Information Particle Filter for Passive Tracking in Sensor Networks
Author :
Xue, Feng ; Liu, Zhong ; Zhang, Xiaorui
Author_Institution :
Naval Univ. of Eng., Wuhan
Abstract :
A decentralized information particle filtering (IPF) algorithm for improving the passive tracking performance and reducing communication amount in wireless sensor networks is proposed in this paper. Dynamic clusters are organized according to the current position of the target, and the decentralized information extended Kalman filter is used to deal with passive tracking problem. The information filter framework is used to incorporate the newest observation into the proposal distribution of the IPF, and detailed implementation steps of the IPF are deduced based on dynamic clustering scheme. Computer simulation is conducted to compare tracking performance and analyze communication amount. Simulation results show that the dynamic clustering structure reduces the communication amount during the tracking, and the IPF has similar good performance in tracking accuracy but lower communication cost than the centralized particle filter.
Keywords :
Kalman filters; nonlinear filters; particle filtering (numerical methods); target tracking; wireless sensor networks; decentralized information particle filter; dynamic clustering scheme; dynamic clusters; extended Kalman filter; passive tracking; sensor networks; wireless sensor networks; Clustering algorithms; Filtering algorithms; Information filtering; Information filters; Particle filters; Particle tracking; Passive filters; Proposals; Target tracking; Wireless sensor networks; Decentralized processing; Particle filter; Sensor networks; Target tracking;
Conference_Titel :
Communications and Networking in China, 2006. ChinaCom '06. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
1-4244-0463-0
Electronic_ISBN :
1-4244-0463-0
DOI :
10.1109/CHINACOM.2006.344690