Low-SNR recognition of UAV-to-ground targets based on micro-Doppler signatures using deep convolutional denoising encoders and deep residual learning
The rapid development of flight control technology has made unmanned aerial vehicles
(UAVs) widely used in high-precision strikes on the battlefield. The premise of this is to …
(UAVs) widely used in high-precision strikes on the battlefield. The premise of this is to …
Multilevel recognition of UAV-to-ground targets based on micro-Doppler signatures and transfer learning of deep convolutional neural networks
Unmanned aerial vehicles (UAVs) are used in different scenarios. The need for intelligent
and accurate recognition of targets using UAV-based radars is increasingly urgent. As …
and accurate recognition of targets using UAV-based radars is increasingly urgent. As …
Deep residual learning in modulation recognition of radar signals using higher-order spectral distribution
Automatically recognizing intra-pulse modulation of radar signals is a significant survival
technique in electronic intelligence systems. To avoid the dependence on feature selection …
technique in electronic intelligence systems. To avoid the dependence on feature selection …
Joint throughput maximization, interference cancellation, and power efficiency for multi-IRS-empowered UAV communications
LF Gu, A Mohajer - Signal, Image and Video Processing, 2024 - Springer
Contemporary mobile communication systems encounter formidable challenges in urban
environments and dead zones, manifesting as issues in reliability, coverage, and quality of …
environments and dead zones, manifesting as issues in reliability, coverage, and quality of …
Research on a signal separation method based on Vold-Kalman filter of improved adaptive instantaneous frequency estimation
Y Li, Z Han, Z Wang - IEEE Access, 2020 - ieeexplore.ieee.org
The fault vibration signal of rotating machinery system under strong background noise has
the characteristics of non-stationary, non-Gaussian and complex components. In view of …
the characteristics of non-stationary, non-Gaussian and complex components. In view of …
基于模糊信息粒化的矿业安全生产态势区间预测
吴孟龙， 叶义成， 胡南燕， 王其虎， 李文， 江慧敏 - 中国安全科学学报, 2021 - cssjj.com.cn
为提高矿业安全生产态势的预测精度, 针对单一预测模型对非平稳非线性时间序列预测精度低,
模型选择困难等问题, 提出一种基于模糊信息粒化(FIG) 的矿业安全生产态势区间预测模型 …
模型选择困难等问题, 提出一种基于模糊信息粒化(FIG) 的矿业安全生产态势区间预测模型 …
Interval prediction of mining work safety situation based on fuzzy information granulation
WU Menglong, YE Yicheng, HU Nanyan… - China Safety Science …, 2021 - cssjj.com.cn
In order to improve prediction accuracy of mining work safety situation, aiming at problems of
low prediction accuracy and difficult model selection for non-stationary nonlinear time series …
low prediction accuracy and difficult model selection for non-stationary nonlinear time series …
Micro-Doppler Parameter Estimation of Ships Based on the Viterbi Algorithm
F Li, S Zhang, L Zhu, H Zhao… - 2022 7th International …, 2022 - ieeexplore.ieee.org
The Viterbi algorithm is a dynamic programming algorithm used to find the Viterbi path-
hidden state sequence that is most likely to generate the observed event sequence. The …
hidden state sequence that is most likely to generate the observed event sequence. The …
ОСНОВЫ ПРИМЕНЕНИЯ И ВОЗМОЖНОСТИ РАЗВИТИЯ ЭФФЕКТА ДОПЛЕРА В ГИДРОАКУСТИКЕ
МА Сабитов - … и перспективы развития современной науки по …, 2021 - elibrary.ru
В данной статье рассмотрены принцип работы и основное применение акустического
доплеровского измерителя течения. Описана эффективность метода, основанного на …
доплеровского измерителя течения. Описана эффективность метода, основанного на …