Set-Membership Adaptive Localization Algorithm with Time-Varying Error Bounds for Underwater Wireless Sensor Networks

Abstract

This paper presents a set-membership adaptive localization algorithm with time-varying error bounds for underwater wireless sensor networks (UWSNs). In large-scale UWSNs, the nonstationary underwater environments, the insufficient prior information of hybrid noise, the small sample size of available distance measurements, and the node mobility all pose severe challenges for localization, and most current schemes are not applicable. Unlike most of the existing approaches, we tackle the multihop localization problem in a set-membership framework based on the consideration that the distance measurement uncertainty can be cast into an unknown but bounded (UBB) context. The principle of our scheme is firstly to use the bootstrap method to build confidence intervals and error bounds from a small sample set of distance measurements and then to determine the positions by a low-complexity interval analysis method as well as an adaptive localization update specification with time-varying error bounds. Simulation results show that our proposed scheme is an effective and efficient localization approach in large-scale UWSNs.