DNN-assisted cooperative localization in vehicular networks

Jewon Eom, Hyowon Kim, Sang Hyun Lee, Sunwoo Kim

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


This work develops a deep-learning-based cooperative localization technique for high localization accuracy and real-time operation in vehicular networks. In cooperative localization, the noisy observation of the pairwise distance and the angle between vehicles causes nonlinear optimization problems. To handle such a nonlinear optimization task at each vehicle, a deep neural network (DNN) technique is to replace a cumbersome solution of nonlinear optimization along with the saving of the computational loads. Simulation results demonstrate that the proposed technique attains some performance gain in localization accuracy and computational complexity as compared to existing cooperative localization techniques.

Original languageEnglish
Article number2758
Issue number14
Publication statusPublished - 2019


  • Cooperative localization
  • Deep neural network
  • Internet of vehicle
  • Multilateration
  • Vehicular networks

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering


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