DNN-Assisted Cooperative Localization in Vehicular Networks

Jewon Eom, Hyowon Kim, Sang Hyun Lee and Sunwoo Kim
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Jewon Eom: Department of Electronics and Computer Engineering, Hanyang University, Seoul 04763, Korea
Hyowon Kim: Department of Electronics and Computer Engineering, Hanyang University, Seoul 04763, Korea
Sang Hyun Lee: School of Electrical Engineering, Korea University, Seoul 02841, Korea
Sunwoo Kim: Department of Electronics and Computer Engineering, Hanyang University, Seoul 04763, Korea

Energies, 2019, vol. 12, issue 14, 1-10

Abstract: 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.

Keywords: cooperative localization; deep neural network; internet of vehicle; multilateration; vehicular networks (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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