南京航空航天大学主页平台管理系统 zhulingzhi--Home-- Low-SNR Recognition of UAV-to-ground Targets Based on Micro-Doppler Signatures Using Deep Convolutional De-noising Encoders and Deep Residual Learning

朱凌智,Associate Professor

朱凌智，副研究员，硕士生导师，分别于2016年6月和2021年6月在南京理工大学获得工学学士和工学博士学位，2021年7月至2024年2月在南京理工大学电子科学与技术博士后流动站从事科学研究，2024年2月加入南京航空航天...more+

Low-SNR Recognition of UAV-to-ground Targets Based on Micro-Doppler Signatures Using Deep Convolutional De-noising Encoders and Deep Residual Learning

Release time:2024-04-15 Hits:

Journal:IEEE Transactions on Geoscience and Remote Sensing

Indexed by:Journal paper

Translation or Not:no

Included Journals:EI、SCI、SCIE

Date of Publication:2022-03-03

Pre One: Lightweight Self-Supervised Recognition of Small-Sample Ships Using Micro-Doppler Signatures and UAV-based UWB Radar Next One: Multilevel Recognition of UAV-to-Ground Targets Based on Micro-Doppler Signatures and Transfer Learning of Deep Convolutional Neural Networks