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Shengming Chang1,2, Youming Li3, Yucheng He4

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Summary
This summary is machine-generated.

This study introduces new methods for underwater target localization using received signal strength (RSS) in acoustic sensor networks. The techniques improve accuracy in both known and unknown target transmit power scenarios.

Keywords:
Cramer–Rao lower bounds (CRLBs)received signal strength (RSS)target localizationunderwater acoustic wireless sensor networks (UWSNs)

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Area of Science:

  • Engineering
  • Computer Science
  • Oceanography

Background:

  • Underwater acoustic wireless sensor networks (UWSNs) face challenges in target localization.
  • Received signal strength (RSS) is a key metric for localization but requires robust algorithms.
  • Target transmit power variations complicate accurate positioning.

Purpose of the Study:

  • To develop novel algorithms for target localization in UWSNs using RSS.
  • To address scenarios with both known and unknown target transmit power.
  • To provide accurate localization solutions in challenging underwater acoustic environments.

Main Methods:

  • Derivation of a weighted least squares (WLS) estimator using RSS approximations.
  • Transformation of the localization problem into a mixed semi-definite programming/second-order cone programming (SD/SOCP) problem.
  • Development of an iterative maximum likelihood (ML) and mixed SD/SOCP algorithm for unknown transmit power cases.

Main Results:

  • A novel WLS estimator was developed for known target transmit power.
  • An iterative ML and mixed SD/SOCP algorithm was presented for unknown target transmit power.
  • Closed-form expressions for Cramer-Rao Lower Bounds (CRLB) on root mean square error (RMSE) were derived for performance evaluation.

Conclusions:

  • The proposed methods demonstrate superior performance compared to existing techniques in underwater acoustic environments.
  • The developed algorithms offer efficient and accurate solutions for RSS-based target localization in UWSNs.
  • The study provides a significant advancement in underwater sensing and navigation capabilities.