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

Yingquan Li, Jiajie Xu, Bodhibrata Mukhopadhyay, Mohamed-Slim Alouini

TL;DR

The paper tackles RSS-based underwater localization when the target’s transmit power is unknown. It introduces GUTP, a weighted RSS approach that uses a generalized trust region subproblem (GTRS) solved via a simple bisection to jointly estimate position and transmit power. The authors derive CRLBs for both known and unknown Pt and show through extensive simulations that GUTP achieves higher localization accuracy and significantly lower computational complexity than SDP-based benchmarks. The method demonstrates robustness to noise characteristics and model biases, highlighting its practical potential for low-cost UWSN deployments. Overall, GUTP offers a scalable, theoretically sound, and efficient solution for underwater target localization with uncertain transmission 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.

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

TL;DR

The paper tackles RSS-based underwater localization when the target’s transmit power is unknown. It introduces GUTP, a weighted RSS approach that uses a generalized trust region subproblem (GTRS) solved via a simple bisection to jointly estimate position and transmit power. The authors derive CRLBs for both known and unknown Pt and show through extensive simulations that GUTP achieves higher localization accuracy and significantly lower computational complexity than SDP-based benchmarks. The method demonstrates robustness to noise characteristics and model biases, highlighting its practical potential for low-cost UWSN deployments. Overall, GUTP offers a scalable, theoretically sound, and efficient solution for underwater target localization with uncertain transmission 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.
Paper Structure (17 sections, 6 equations, 9 figures, 3 tables)

This paper contains 17 sections, 6 equations, 9 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Background and Motivations
  3. Related Works
  4. Contributions
  5. Channel model
  6. Weighted RSS measurements
  7. Localization technique with unknown transmit power
  8. Cramer-Rao Lower Bound (CRLB)
  9. Performance analysis
  10. Performance in Estimating the Location
  11. Performance in Estimating the Transmit Power
  12. Effect of the Number of Anchor Nodes
  13. Effect of the PLE and absorption coefficient
  14. Effect of Noise Characteristics on Localization Performance
  15. Sensitivity Analysis to Bias in Prior Knowledge of Model Parameters
  16. ...and 2 more sections

Figures (9)

  • Figure 1: Network architecture of the UWSN for target localization.
  • Figure 2: Illustration of the effect of link distance on distance estimation errors under the same noise level.
  • Figure 3: The evaluated UWSN topology.
  • Figure 4: NRMSE of location estimate as a function of $\sigma$.
  • Figure 5: NRMSE of transmit power estimate as a function of $\sigma$.
  • ...and 4 more figures