TY - GEN
T1 - A Semantic Cognition Enhancment Network for Interference Detection in Sentinel-1 SAR Image
AU - Li, Jieshuang
AU - Tao, Mingliang
AU - Zhang, Xiang
AU - Su, Jia
AU - Fan, Yifei
AU - Wang, Ling
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - The existence of radio frequency interference (RFI) can cause partial image degradation, image interpretation errors, and parameter extraction deviations. The precise detection and localization of the interference is the premise step for successful mitigation. However, the shape of weak interference is changeable and lacks a unified mathematical model, while its energy difference with the surrounding background is very small, which makes it difficult to be detected in complex environment. This paper proposes a semantic cognitive enhancement network for RFI detection in Sentinel-1 SAR image. Through the fusion of dilated convolution, cross-layer connection and self-attention mechanism, it can effectively improve the detection performance of weak interference under the condition of small sample training.
AB - The existence of radio frequency interference (RFI) can cause partial image degradation, image interpretation errors, and parameter extraction deviations. The precise detection and localization of the interference is the premise step for successful mitigation. However, the shape of weak interference is changeable and lacks a unified mathematical model, while its energy difference with the surrounding background is very small, which makes it difficult to be detected in complex environment. This paper proposes a semantic cognitive enhancement network for RFI detection in Sentinel-1 SAR image. Through the fusion of dilated convolution, cross-layer connection and self-attention mechanism, it can effectively improve the detection performance of weak interference under the condition of small sample training.
KW - Sentinel-1
KW - Synthetic aperture radar
KW - interference detection
KW - radio frequency interference
KW - semantic cognition network
UR - https://www.scopus.com/pages/publications/85181070100
U2 - 10.1109/Radar53847.2021.10027879
DO - 10.1109/Radar53847.2021.10027879
M3 - 会议稿件
AN - SCOPUS:85181070100
T3 - Proceedings of the IEEE Radar Conference
SP - 1923
EP - 1926
BT - 2021 CIE International Conference on Radar, Radar 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 CIE International Conference on Radar, Radar 2021
Y2 - 15 December 2021 through 19 December 2021
ER -