Login / Signup

A Weighted and Distributed Algorithm for Range-Based Multi-Hop Localization Using a Newton Method.

Jose Diaz-RomanBoris MederosErnesto SifuentesRafael Gonzalez-LandaetaJuan Cota-Ruiz
Published in: Sensors (Basel, Switzerland) (2021)
Wireless sensor networks are used in many location-dependent applications. The location of sensor nodes is commonly carried out in a distributed way for energy saving and network robustness, where the handling of these characteristics is still a great challenge. It is very desirable that distributed algorithms invest as few iterations as possible with the highest accuracy on position estimates. This research proposes a range-based and robust localization method, derived from the Newton scheme, that can be applied over isotropic and anisotropic networks in presence of outliers in the pair-wise distance measurements. The algorithm minimizes the error of position estimates using a hop-weighted function and a scaling factor that allows a significant improvement on position estimates in only few iterations. Simulations demonstrate that our proposed algorithm outperforms other similar algorithms under anisotropic networks.
Keyphrases
  • machine learning
  • deep learning
  • neural network
  • magnetic resonance
  • network analysis
  • contrast enhanced
  • magnetic resonance imaging
  • finite element
  • computed tomography
  • sentinel lymph node
  • early stage