Coarse-to-Fine Localization of Underwater Acoustic Communication Receivers

Abstract

For underwater acoustic (UWA) communication in sensor networks, the sensing information can only be interpreted meaningfully when the location of the sensor node is known. However, node localization is a challenging problem. Global Navigation Satellite Systems (GNSS) used in terrestrial applications do not work underwater. In this paper, we propose and investigate techniques based on matched field processing for localization of a single-antenna UWA communication receiver relative to one or more transmit antennas. Firstly, we demonstrate that a non-coherent ambiguity function (AF) allows significant improvement in the localization performance compared to the coherent AF previously used for this purpose, especially at high frequencies typically used in communication systems. Secondly, we propose a two-step (coarse-to-fine) localization technique. The second step provides a refined spatial sampling of the AF in the vicinity of its maximum found on the coarse space grid covering an area of interest (in range and depth), computed at the first step. This technique allows high localization accuracy and reduction in complexity and memory storage, compared to single step localization. Thirdly, we propose a joint refinement of the AF around several maxima to reduce outliers. Numerical experiments are run for validation of the proposed techniques.

An Oceano-Acoustic Simulation Framework for the Design of Lagrangian Systems Drifting in Mesoscale and Sub-Mesoscale Currents

“…Ranging is commonly solved as an inverse problem [24]- [27]. Based on the estimates Ln , (α n,l , τ 0 n,l , ˆ n,l ) l=0,.., Ln−1 , the estimated channel…”

“…A coherent processor that keeps the phase information of the channel and a noncoherent processor that removes the phase information from the comparison. They can be expressed, respectively, as [27]…”