Article

Collaborative tracking via particle filter in wireless sensor networks

Journal of Electronics (China) 04/2012; 25(3):311-318. DOI:10.1007/s11767-006-0277-0 pp.311-318

ABSTRACT Target tracking is one of the main applications of wireless sensor networks. Optimized computation and energy dissipation
are critical requirements to save the limited resource of the sensor nodes. A framework and analysis for collaborative tracking
via particle filter are presented in this paper. Collaborative tracking is implemented through sensor selection, and results
of tracking are propagated among sensor nodes. In order to save communication resources, a new Gaussian sum particle filter,
called Gaussian sum quasi particle filter, to perform the target tracking is presented, in which only mean and covariance
of mixands need to be communicated. Based on the Gaussian sum quasi particle filter, a sensor selection criterion is proposed,
which is computationally much simpler than other sensor selection criterions. Simulation results show that the proposed method
works well for target tracking.

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Keywords

collaborative
 
covariance
 
critical requirements
 
Gaussian sum quasi particle filter
 
limited resource
 
main applications
 
new Gaussian sum particle filter
 
Optimized computation
 
particle filter
 
sensor nodes
 
sensor selection
 
sensor selection criterion
 
sensor selection criterions
 
wireless sensor networks