[HTML][HTML] Frequency-Modulated Continuous-Wave Radar Perspectives on Unmanned Aerial Vehicle Detection and Classification: A Primer for Researchers with …
Unmanned Aerial Vehicles (UAVs) represent a rapidly increasing technology with profound
implications for various domains, including surveillance, security, and commercial …
implications for various domains, including surveillance, security, and commercial …
SNR‐dependent drone classification using convolutional neural networks
Radar sensing offers a method of achieving 24‐h all‐weather drone surveillance, but in
order to be maximally effective, systems need to be able to discriminate between birds and …
order to be maximally effective, systems need to be able to discriminate between birds and …
A survey on detection, classification, and tracking of aerial threats using radar and communications systems
[HTML][HTML] Review of the technology, development and applications of holographic staring radar
GUO Rui, Z Yue, T Biao, X Yu, HU Jun, XU Shiyou… - 雷达学报, 2022 - radars.ac.cn
Holographic staring radar is an array radar that continuously looks everywhere and performs
multiple functions simultaneously instead of sequentially. First, this paper clarifies the …
multiple functions simultaneously instead of sequentially. First, this paper clarifies the …
Convolutional neural networks for robust classification of drones
In order to be effective, radar drone surveillance systems need to be able to discriminate
between birds and drones. In this work, convolutional neural networks (CNNs) are used to …
between birds and drones. In this work, convolutional neural networks (CNNs) are used to …
UAVs and birds classification using robust coordinate attention synergy residual split-attention network based on micro-Doppler signature measurement by using L …
Develo** unmanned aerial vehicles (UAVs) and birds surveillance technologies to
produce accurate descriptions and achieve high classification accuracy is critical in the field …
produce accurate descriptions and achieve high classification accuracy is critical in the field …
Model-aided drone classification using convolutional neural networks
Classifiers using convolutional neural networks (CNNs) often yield high accuracies on
samples that come from the same distribution as the training data. In this study we evaluate …
samples that come from the same distribution as the training data. In this study we evaluate …
Development of quantum enabled staring radar with low phase noise
Staring radar provide a significant capability against the detection of low observable targets
such as drones and birds. Their performance in strong urban clutter can be impacted by …
such as drones and birds. Their performance in strong urban clutter can be impacted by …
Radar discrimination of small airborne targets through kinematic features and machine learning
This work studies binary classification problem for small airborne targets (drones vs other)
by means of their trajectory analysis. For this purpose a set of the kinematic features …
by means of their trajectory analysis. For this purpose a set of the kinematic features …