TY - GEN
T1 - Physical-aware Radar Image Synthesis with Projective Network
AU - Song, Qian
AU - Xu, Feng
AU - Zhu, Xiao Xiang
N1 - Publisher Copyright:
© 2021 URSI.
PY - 2021/8/28
Y1 - 2021/8/28
N2 - This paper proposed a new network module named as projection network, which explicitly combined radar's projection process with trainable network. It assumes that each 2D radar cross section (RCS) map is a projection of a 3D RCS map. And it models the projection mechanism as a differentiable layer, so that it can be integrated with other neural network layers, such as convolutional and pooling layers. The proposed model is consistent with radar projection process, hence effects such as layover is considered. It is designed and used specifically for radar applications. This paper applied the proposed network on radar image synthesis, and the simulation results showed great potential of projective network.
AB - This paper proposed a new network module named as projection network, which explicitly combined radar's projection process with trainable network. It assumes that each 2D radar cross section (RCS) map is a projection of a 3D RCS map. And it models the projection mechanism as a differentiable layer, so that it can be integrated with other neural network layers, such as convolutional and pooling layers. The proposed model is consistent with radar projection process, hence effects such as layover is considered. It is designed and used specifically for radar applications. This paper applied the proposed network on radar image synthesis, and the simulation results showed great potential of projective network.
UR - http://www.scopus.com/inward/record.url?scp=85118244789&partnerID=8YFLogxK
U2 - 10.23919/URSIGASS51995.2021.9560559
DO - 10.23919/URSIGASS51995.2021.9560559
M3 - Conference contribution
AN - SCOPUS:85118244789
T3 - 2021 34th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2021
BT - 2021 34th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 34th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2021
Y2 - 28 August 2021 through 4 September 2021
ER -