Estimating the Magnitude and Phase of Automotive Radar Signals Under Multiple Interference Sources With Fully Convolutional Networks
Radar sensors are gradually becoming a wide-spread equipment for road vehicles, playing a crucial role in autonomous driving and road safety. The broad adoption of radar sensors increases the chance of interference among sensors from different vehicles, generating corrupted range profiles and range-...
Enregistré dans:
Auteurs principaux: | Nicolae-Catalin Ristea, Andrei Anghel, Radu Tudor Ionescu |
---|---|
Format: | article |
Langue: | EN |
Publié: |
IEEE
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/ed52fac519074e77a4cb8fc081f2c27c |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Sparse Automotive MIMO Radar for Super-Resolution Single Snapshot DOA Estimation With Mutual Coupling
par: Navid Amani, et autres
Publié: (2021) -
MATERIALS FOR AUTOMOTIVE INDUSTRY AND THEIR INFLUENCE ON THE DYNAMICS OF A CAR CRASH
par: NICOLAE NAVODARIU, et autres
Publié: (2019) -
Single-Channel FMCW-Radar-Based Multi-Passenger Occupancy Detection Inside Vehicle
par: Heemang Song, et autres
Publié: (2021) -
Surrounding Objects Detection and Tracking for Autonomous Driving Using LiDAR and Radar Fusion
par: Ze Liu, et autres
Publié: (2021) -
Review on Frequency Agile Radar Seeker
par: Quan Yinghui, Fang Wen, Gao Xia, Ruan Feng, Li Yachao, Xing Mengdao
Publié: (2021)