DNN-Assisted Cooperative Localization in Vehicular Networks

Citations

WEB OF SCIENCE

13
Citations

SCOPUS

14

초록

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.

키워드

cooperative localization; deep neural network; internet of vehicle; multilateration; vehicular networks; NEURAL-NETWORKS; BELIEF PROPAGATION; NAVIGATION
제목
DNN-Assisted Cooperative Localization in Vehicular Networks
저자
Eom, Jewon; Kim, Hyowon; Lee, Sang Hyun; Kim, Sun woo
DOI
10.3390/en12142758
발행일
2019-07
유형
Article
저널명
Energies
권
12
호
14

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