An indicator kriging method for distributed estimation in wireless sensor networks

Abstract

SUMMARYThe problem of distributed estimation in a wireless sensor network with unknown observation noise distribution is investigated, where each sensor only sends quantized data to a fusion center. The sensing field is modeled as a spatially random field. The objective was to accurately estimate a hidden parameter at the location where no sensor exists, while minimizing the total energy consumption. Driven by the lack of a prior knowledge of the sensing field and the existence of some outliers, an indicator kriging estimator is developed for distributed estimation under imperfect communication channels between the sensors and the fusion center. The tradeoff between estimation performance and energy consumption is formulated as an optimization problem, and a global search algorithm is proposed to approximate the solution. The results show that the proposed indicator kriging estimator achieves better performance than the inverse distance estimator and the simple averaging estimator. Moreover, the proposed search algorithm can schedule the sensors to reach the tradeoff. Copyright © 2012 John Wiley & Sons, Ltd.