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NLOS Identification and Positioning Algorithm Based on Localization Residual in Wireless Sensor Networks.

Jingyu Hua1, Yejia Yin2, Weidang Lu3

  • 1Zhejiang Gongshang University, Hangzhou 310018, China. eehjy@163.com.

Sensors (Basel, Switzerland)
|September 13, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a new algorithm for wireless sensor network localization that accurately identifies and excludes non-line-of-sight signals. This method improves target localization accuracy in challenging environments.

Keywords:
localization residualnon-line-of-sight errorwireless localizationwireless sensor network

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Area of Science:

  • Wireless Sensor Networks (WSN)
  • Localization Algorithms
  • Signal Propagation

Background:

  • Traditional WSN localization algorithms suffer performance degradation in non-line-of-sight (NLOS) environments.
  • Existing NLOS mitigation methods, such as optimization-based and NLOS modeling, present challenges like high complexity or environmental sensitivity.

Purpose of the Study:

  • To develop a simple and accurate algorithm for target localization in WSNs, specifically addressing the challenges posed by NLOS propagation.
  • To effectively identify and mitigate the impact of NLOS anchor nodes (ANs) on localization accuracy.

Main Methods:

  • A novel NLOS identification and localization algorithm is proposed, based on residual analysis.
  • Anchor nodes are grouped, and intermediate position estimates are obtained using traditional methods.
  • NLOS anchor nodes (NLOS-ANs) are identified via a hypothesis test using localization residuals, requiring at least two line-of-sight (LOS) ANs.

Main Results:

  • The proposed algorithm successfully identifies NLOS-ANs.
  • Localization accuracy is significantly improved by utilizing only LOS-propagating anchor nodes for final position estimation.
  • The method demonstrates high accuracy provided a minimum of two LOS-ANs are available.

Conclusions:

  • The developed residual analysis-based algorithm offers a robust solution for WSN target localization in the presence of NLOS conditions.
  • Accurate localization is achievable by effectively distinguishing between LOS and NLOS signals.
  • The algorithm's simplicity and effectiveness make it a valuable contribution to WSN research.