%0 Journal Article
%T Adaptive Non-myopic Quantizer Design for Target Tracking in Wireless Sensor Networks
%A Sijia Liu
%A Engin Masazade
%A Xiaojing Shen
%A Pramod K. Varshney
%J Statistics
%D 2013
%I arXiv
%X In this paper, we investigate the problem of nonmyopic (multi-step ahead) quantizer design for target tracking using a wireless sensor network. Adopting the alternative conditional posterior Cramer-Rao lower bound (A-CPCRLB) as the optimization metric, we theoretically show that this problem can be temporally decomposed over a certain time window. Based on sequential Monte-Carlo methods for tracking, i.e., particle filters, we design the local quantizer adaptively by solving a particlebased non-linear optimization problem which is well suited for the use of interior-point algorithm and easily embedded in the filtering process. Simulation results are provided to illustrate the effectiveness of our proposed approach.
%U http://arxiv.org/abs/1303.2060v2