Open AccessMulti-radar collaborative networking method based on T-GCN
Author(s) -
Peng Liu,
Youlong Xu,
Jing Ma,
Jun Liang,
Xiao Han,
Cong Yang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1976/1/012037
Subject(s) - radar , computer science , convolutional neural network , graph , artificial intelligence , artificial neural network , context (archaeology) , telecommunications , geography , theoretical computer science , archaeology
Multi-radar collaborative networking is the development direction and research hotspot of radar detection technology. In recent years, with the rise of artificial intelligence, researchers have introduced neural networks and other artificial intelligence methods into multi-radar collaborative networking and achieved remarkable results. In this work, we abstract the radar network as an un-weighted graph, and then introduce the GCN, and combine the characteristics of the GRU with the temporal context, apply the Temporal Graph Convolutional Network to multi-radar collaborative network. We solve the problem of low efficiency and slow speed of radar network without data fusion.