@inproceedings{08185bc967034a85b6aa3f5b05b73d00,
title = "Weak Target Detection based on Deep Neural Network under Sea Clutter Background",
abstract = "To upgrade the performance of the traditional radar target detecting method based on one certain threshold, this paper applies the deep learning network into target detection field, which regards radar target detection as a binary signal classification question. Since sea clutter exhibits non-stationary characteristics with high sea state condition, fractal properties of sea clutter are considered for target detection. In addition, fractal parameters of autoregressive (AR) spectrum are regarded as the feature inputs for deep learning network. Finally, real radar sea clutter data are applied for training the deep learning neutral network, and several datasets are selected to test the detecting performance of the network. From the binary classification results, the proposed method based on deep learning network performs a better detecting performance than traditional CFAR and fractal methods.",
keywords = "deep learning, fractal, Sea clutter, target detecting",
author = "Yifei Fan and Shuting Tang and Siyuan Zhao and Xiang Zhang and Mingliang Tao and Jia Su",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 3rd IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2020 ; Conference date: 13-11-2020 Through 15-11-2020",
year = "2020",
month = nov,
day = "13",
doi = "10.1109/ICEICT51264.2020.9334284",
language = "英语",
series = "ICEICT 2020 - IEEE 3rd International Conference on Electronic Information and Communication Technology",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "538--540",
booktitle = "ICEICT 2020 - IEEE 3rd International Conference on Electronic Information and Communication Technology",
}