Automotive radar—From first efforts to future systems

C Waldschmidt, J Hasch… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Although the beginning of research on automotive radar sensors goes back to the 1960s,
automotive radar has remained one of the main drivers of innovation in millimeter wave …

Convolutional neural network-based radar jamming signal classification with sufficient and limited samples

G Shao, Y Chen, Y Wei - IEEE Access, 2020 - ieeexplore.ieee.org
Jamming is a big threat to radar system survival and anti-jamming is a part of the solution.
The classification of radar jamming signal is the first step toward to anti-jamming. Recently …

Robust gait recognition based on deep cnns with camera and radar sensor fusion

Y Shi, L Du, X Chen, X Liao, Z Yu, Z Li… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
In recent years, gait recognition has emerged as an important and promising solution for
human identification. Generally, gait recognition is based on a single type of sensor, such as …

A short-range FMCW radar-based approach for multi-target human-vehicle detection

E Tavanti, A Rizik, A Fedeli, DD Caviglia… - … on Geoscience and …, 2021 - ieeexplore.ieee.org
In this article, a new microwave-radar-based technique for short-range detection and
classification of multiple human and vehicle targets crossing a monitored area is proposed …

Cone-shaped space target inertia characteristics identification by deep learning with compressed dataset

S Wang, M Li, T Yang, X Ai, J Liu… - … on Antennas and …, 2022 - ieeexplore.ieee.org
An effective method for identifying inertia characteristics of cone-shaped space target based
on deep learning is proposed. The inertia ratio is determined by the time-varying scattering …

Micro-motion classification of flying bird and rotor drones via data augmentation and modified multi-scale cnn

X Chen, H Zhang, J Song, J Guan, J Li, Z He - Remote Sensing, 2022 - mdpi.com
Aiming at the difficult problem of the classification between flying bird and rotary-wing drone
by radar, a micro-motion feature classification method is proposed in this paper. Using K …

Intelligent reflecting surface-based non-LOS human activity recognition for next-generation 6G-enabled healthcare system

U Saeed, SA Shah, MZ Khan, AA Alotaibi, T Althobaiti… - Sensors, 2022 - mdpi.com
Human activity monitoring is a fascinating area of research to support autonomous living in
the aged and disabled community. Cameras, sensors, wearables, and non-contact …

Efficient discrimination of ballistic targets with micromotions

IO Choi, SH Park, M Kim, KB Kang… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The micro-Doppler phenomenon in the echo signal received from a ballistic target (BT) with
micro-motion is commonly used to discriminate BTs such as warheads and decoys. The joint …

Potential active shooter detection based on radar micro-Doppler and range-Doppler analysis using artificial neural network

Y Li, Z Peng, R Pal, C Li - IEEE Sensors Journal, 2018 - ieeexplore.ieee.org
This paper presents a detection method of remotely identifying a potential active shooter
with a concealed rifle/shotgun based on radar micro-Doppler and range-Doppler signature …

Single-frame vulnerable road users classification with a 77 GHz FMCW radar sensor and a convolutional neural network

R Pérez, F Schubert, R Rasshofer… - 2018 19th International …, 2018 - ieeexplore.ieee.org
Road traffic accidents accounted in 2013 for over a million deaths worldwide. Pedestrians
and cyclists are especially vulnerable in road accidents and therefore it is essential to …