TY - GEN
T1 - Spectral Gap Extrapolation and Radio Frequency Interference Suppression Using 1D UNets
AU - Nair, Arun Asokan
AU - Rangamani, Akshay
AU - Nguyen, Lam H.
AU - Bell, Muyinatu A.Lediju
AU - Tran, Trac D.
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/5/7
Y1 - 2021/5/7
N2 - Modern ultra-wideband (UWB) radar systems transmit a wide range of frequencies, spanning hundreds of MHz to a few GHz, to achieve improved penetration depth and narrower pulse width. A common challenge faced is the presence of other commercial transmission equipment operating in the same band, causing radio frequency interference (RFI). To overcome this RFI issue, radar systems have been developed to either avoid operating in bands with RFI or suppress the RFI after reception. In this work, we examine both families of operation and demonstrate that 1D convolutional neural networks based on the UNet architecture can provide powerful signal enhancement capabilities on raw UWB radar data. The model is trained purely on simulated data and translated to real UWB data, achieving impressive results compared to traditional sparse-recovery baseline algorithms.
AB - Modern ultra-wideband (UWB) radar systems transmit a wide range of frequencies, spanning hundreds of MHz to a few GHz, to achieve improved penetration depth and narrower pulse width. A common challenge faced is the presence of other commercial transmission equipment operating in the same band, causing radio frequency interference (RFI). To overcome this RFI issue, radar systems have been developed to either avoid operating in bands with RFI or suppress the RFI after reception. In this work, we examine both families of operation and demonstrate that 1D convolutional neural networks based on the UNet architecture can provide powerful signal enhancement capabilities on raw UWB radar data. The model is trained purely on simulated data and translated to real UWB data, achieving impressive results compared to traditional sparse-recovery baseline algorithms.
KW - convolutional neural network
KW - radio frequency interference suppression
KW - Spectral gap extrapolation
KW - ultra-wideband radar
UR - http://www.scopus.com/inward/record.url?scp=85112417250&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85112417250&partnerID=8YFLogxK
U2 - 10.1109/RadarConf2147009.2021.9455241
DO - 10.1109/RadarConf2147009.2021.9455241
M3 - Conference contribution
AN - SCOPUS:85112417250
T3 - IEEE National Radar Conference - Proceedings
BT - 2021 IEEE Radar Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE Radar Conference, RadarConf 2021
Y2 - 8 May 2021 through 14 May 2021
ER -