Interference Suppression for Radar Signal using 2D UNet based on Semantic Segmentation

Jiawang Li, Yanyun Gong, Mingliang Tao, Zhengyi Zhang, Jia Su, Yifei Fan

科研成果: 书/报告/会议事项章节会议稿件同行评审

3 引用 (Scopus)

摘要

The wide application of automotive radars significantly increases the possibility of mutual interference. Interference can lead to false detections such as ghost objects and missed detections, with serious threats to vehicle and pedestrian safety. In this paper, we build an end-to-end interference suppression model using 2D UNet. The UNet takes the input through the encoder with down-sampling to get a feature smaller than the initial data, and then inputs this feature into the decoder and reduces it to the clean signal, thus achieving interference suppression. By providing the network with clean data and interference-contaminated data, the network can be well trained to mitigate the interference artifacts. Experimental results show that the proposed scheme could achieve superior performance compared with traditional signal processing algorithms, in which the target peak was preserved and the signal-to-noise ratio (SINR) was significantly improved.

源语言英语
主期刊名2022 IEEE 5th International Conference on Electronic Information and Communication Technology, ICEICT 2022
出版商Institute of Electrical and Electronics Engineers Inc.
603-606
页数4
ISBN(电子版)9781665472111
DOI
出版状态已出版 - 2022
活动5th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2022 - Hefei, 中国
期限: 21 8月 202223 8月 2022

出版系列

姓名2022 IEEE 5th International Conference on Electronic Information and Communication Technology, ICEICT 2022

会议

会议5th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2022
国家/地区中国
Hefei
时期21/08/2223/08/22

指纹

探究 'Interference Suppression for Radar Signal using 2D UNet based on Semantic Segmentation' 的科研主题。它们共同构成独一无二的指纹。

引用此