Consensus estimation‐based target localization in underwater acoustic sensor networks

Abstract

SummaryTarget localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs). However, the resource‐constrained property of an underwater environment such as noise makes target localization a challenging problem. This paper considers a consensus estimation‐based approach to the target localization problem in UASNs. To detect and acquire the position of the target, a hybrid architecture is applied to UASNs, where autonomous underwater vehicles provide self‐location and clock synchronization for sensor nodes. Built on this architecture, a trilateration method coupled with a regional optimal solution is provided to estimate the rough localization of a target. Furthermore, a consensus estimation‐based algorithm is designed for the regional optimal solution, such that localization accuracy is improved. In the presence of measurement and communication noises, localization error and asymptotic unbiasedness for the estimation algorithm are also investigated. Finally, simulation results show that the proposed localization approach can avoid the occurrence of no‐solution while improving the localization accuracy. In addition, the hybrid communication architecture can reduce the number of transmissions compared with egalitarian decentralized networks. Copyright © 2016 John Wiley & Sons, Ltd.