3-D RSSD Localization Under Mixed Gaussian Noise and NLOS Environments in UWSNs

Abstract

This article presents a robust 3-D received signal strength difference (RSSD) localization algorithm under mixed Gaussian noise in underwater wireless sensor networks (UWSNs) with nonline-of-sight (NLOS) paths. To mitigate the adverse effects, concurrent to absorption and path losses on accurate underwater localization, an Efficient RSSD-based Iterative Estimator (ERIE) in mixed Gaussian noise and NLOS environments is proposed. First, the corresponding nonconvex problem in such environments is formulated, and the direct solution to this problem is not tractable unfortunately. Considering underwater acoustic signal attenuation, an RSSD-based min-max strategy is designed to transform it into a problem minimizing the worst-case loss, combined with the Huber cost function, constitutes a Huber function-based equivalent problem (H-ADMM) solved by alternating direction method of multipliers (ADMM). A compensation matrix is designed based on the H-ADMM solution to compensate for the bias introduced by the transformation, and the corresponding Cramér-Rao lower bound (CRLB) is derived to provide a performance benchmark. Numerical results indicate that the proposed approach achieves a higher localization accuracy than state-of-the-art methods.