@inproceedings{189f982da4fb4b0cb30cff586a69c699,
title = "Ground Background Clutter Recognition Based on Fully Convolutional Neural Network",
abstract = "Accurate and robust recognition of background clutter is essential for radar target detection. Aiming at the problems that existing clutter recognition methods have low accuracy and poor robustness, a background clutter recognition method based on novel Fully Convolutional Neural Network (FCNN) is proposed. FCNN is trained and tested based on the simulated ground clutter Range-Doppler (R-D) spectra. Experimental results demonstrate that FCNN is significantly superior to the existing background clutter recognition models in terms of clutter classification accuracy or time complexity. In addition, FCNN can better adapt to clutter recognition under low clutter-to-noise ratio (CNR) scenarios. Finally, we verify the effectiveness of the CFAR detector based on clutter recognition.",
keywords = "Range-Doppler, background clutter, clutter recognition, fully convolutional neural network",
author = "Chang Liu and Ping Lang and Xiongjun Fu and Jian Dong and Mingling Li and Xinyue Qi",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 CIE International Conference on Radar, Radar 2021 ; Conference date: 15-12-2021 Through 19-12-2021",
year = "2021",
doi = "10.1109/Radar53847.2021.10028271",
language = "English",
series = "Proceedings of the IEEE Radar Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1850--1853",
booktitle = "2021 CIE International Conference on Radar, Radar 2021",
address = "United States",
}