Low-Complexity RSS-based Underwater Localization with Unknown Transmit Power

TL;DR

This paper introduces GUTP, a low-complexity RSS-based underwater localization method that jointly estimates target position and transmit power without prior power knowledge, outperforming existing techniques in accuracy and efficiency.

Contribution

It proposes a novel GUTP method using weighted RSS and GTRS, eliminating the need for transmit power prior knowledge and reducing computational complexity.

Findings

GUTP achieves higher localization accuracy than SDP-based methods.

GUTP has significantly lower computational complexity.

The method effectively estimates both position and transmit power.

Abstract

Underwater wireless sensor networks (UWSNs) have received significant attention due to their various applications, with underwater target localization playing a vital role in enhancing network performance. Given the challenges and high costs associated with UWSN deployments, Received Signal Strength (RSS)-based localization offers a viable solution due to its minimal hardware requirements and cost-effectiveness. In this paper, we assign distance-based weights to RSS measurements, providing higher reliability to closer anchor nodes. Using the weighted RSS measurements and generalized trust region subproblem (GTRS), we propose the GTRS-based localization technique with Unknown Transmit Power (GUTP), which can be solved by a simple bisection method. Unlike conventional localization methods that require prior knowledge of the target node's transmit power, GUTP jointly estimates both the location and transmit power of the target node, broadening its practical use. Additionally, we derive the Cramer-Rao lower bounds (CRLBs) for RSS-based underwater localization with known and unknown transmit power, respectively. Extensive simulations demonstrate that GUTP achieves enhanced accuracy and significantly lower computational complexity in estimating the target node's location and transmit power compared to existing semidefinite programming (SDP)-based techniques.