@inproceedings{e1beddd3cad94fcd8da1445e0d3394e6,
title = "Corner Reflector Identification Based on Improved Temporal Convolutional Network and LSTM",
abstract = "The corner reflector is a typical passive jamming. To address the problems of relying on manual feature extraction and low accuracy of small samples in existing corner reflector identification methods, this paper proposes a method based on a combination of improved temporal convolutional network (TCN) and long short-term memory (LSTM). The proposed method uses TCN to extract deeper features of high-resolution range profile (HRRP) sequences, replaces the original cross-layer connection of TCN with dense connection, and utilizes LSTM to extract long-distance dependence information. Experimental results show that the identification accuracy of this fusion network reaches 99.12%, and the accuracy and robustness are better than the original model.",
keywords = "LSTM, TCN, anti-jamming, corner reflector",
author = "Shuyan Guan and Xiongjun Fu and Jian Dong",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 8th International Conference on Signal and Image Processing, ICSIP 2023 ; Conference date: 08-07-2023 Through 10-07-2023",
year = "2023",
doi = "10.1109/ICSIP57908.2023.10270855",
language = "English",
series = "2023 8th International Conference on Signal and Image Processing, ICSIP 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "957--962",
booktitle = "2023 8th International Conference on Signal and Image Processing, ICSIP 2023",
address = "United States",
}