Robust calibration for localization in clustered wireless sensor networks

This paper presents a robust calibration procedure for a clustered wireless sensor network. The calibration problem is often formulated as a parameter estimation problem using a linear calibration model. For reducing or eliminating unwanted influences of measurement corruptions or outliers on parameter estimation, a robust regression estimator is a natural choice. In order to solve a robust estimation problem more efficiently, we utilize cluster structure in a network configuration and decompose a large network into smaller subsystems that can be solved much faster. To this end, we present two algorithms for a robust calibration procedure. Two examples are presented to illustrate how the proposed methods enable robust calibration in a sensor network.