DNN-Assisted Cooperative Localization in Vehicular Networks

被引：12

作者：

Eom, Jewon ^{[1
]}

Kim, Hyowon ^{[1
]}

Lee, Sang Hyun ^{[2
]}

Kim, Sunwoo ^{[1
]}

机构：

[1] Hanyang Univ, Dept Elect & Comp Engn, Seoul 04763, South Korea

[2] Korea Univ, Sch Elect Engn, Seoul 02841, South Korea

来源：

ENERGIES | 2019年 / 12卷 / 14期

关键词：

cooperative localization; deep neural network; internet of vehicle; multilateration; vehicular networks; NEURAL-NETWORKS; BELIEF PROPAGATION; NAVIGATION;

D O I：

10.3390/en12142758

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

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.

引用

页数：10