Localization of mobile targets in a wireless sensor network using Diffusion Least Mean Square algorithm based on Huber loss function

Articles in Press

Document Type : Original Article

Authors

1 Faculty of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad, Iran

2 Department of Computer Engineering, Salman Institute of Higher Education, Mashhad, Iran

3 Department of Biomedical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran

Abstract

Localization of mobile targets is one of the important topics in wireless sensor networks. The challenge lies in deploying techniques capable of estimating the subject's location amidst system noise, with minimal deviation from the actual location. In this paper, we propose a robust variant of the diffusion least mean square algorithm. This version involves distributing the estimation of the target's location across network nodes, facilitated by the pseudo-Huber's loss function. Through this method, the accuracy of estimation in localization and tracking the target improves even in the presence of various noise types. The paper formulates target location using two criteria: received signal strength and signal propagation time, based on the proposed algorithm within an adaptive filter network. Experimental results highlight the algorithm's capability to enhance the accuracy of localization and tracking operations. This improvement remains consistent across wireless sensor network scenarios influenced by both Gaussian and non-Gaussian noises, with varying signal-to-noise ratios.

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Soft Computing Journal

Articles in Press, Accepted Manuscript
Available Online from 21 September 2023

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History

  • Receive Date: 04 April 2023
  • Revise Date: 27 August 2023
  • Accept Date: 04 September 2023

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