[HTML][HTML] Radar target characterization and deep learning in radar automatic target recognition: A review
W Jiang, Y Wang, Y Li, Y Lin, W Shen - Remote Sensing, 2023 - mdpi.com
Radar automatic target recognition (RATR) technology is fundamental but complicated
system engineering that combines sensor, target, environment, and signal processing …
system engineering that combines sensor, target, environment, and signal processing …
Radar HRRP target recognition with deep networks
B Feng, B Chen, H Liu - Pattern Recognition, 2017 - Elsevier
Feature extraction is the key technique for radar automatic target recognition (RATR) based
on high-resolution range profile (HRRP). Traditional feature extraction algorithms usually …
on high-resolution range profile (HRRP). Traditional feature extraction algorithms usually …
Radar HRRP target recognition based on higher order spectra
Radar high-resolution range profile (HRRP) is very sensitive to time-shift and target-aspect
variation; therefore, HRRP-based radar automatic target recognition (RATR) requires …
variation; therefore, HRRP-based radar automatic target recognition (RATR) requires …
Mathematical problems in radar inverse scattering
B Borden - Inverse Problems, 2001 - iopscience.iop.org
The problem of all-weather noncooperative target recognition is of considerable interest to
both defense and civil aviation agencies. Furthermore, the discipline of radar inverse …
both defense and civil aviation agencies. Furthermore, the discipline of radar inverse …
Automatic target recognition using sequences of high resolution radar range-profiles
SP Jacobs, JA O'Sullivan - IEEE Transactions on aerospace …, 2000 - ieeexplore.ieee.org
In this paper, we address the problem of joint tracking and recognition of a target using a
sequence of high resolution radar (HRR) range-profiles. The likelihood function for the …
sequence of high resolution radar (HRR) range-profiles. The likelihood function for the …
Machine learning-based target classification for MMW radar in autonomous driving
X Cai, M Giallorenzo… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Millimeter-wave (MMW) radar sensors are considered key components of autonomous
vehicles. Because of the performance degeneration of cameras and lidars under inclement …
vehicles. Because of the performance degeneration of cameras and lidars under inclement …
A new feature vector using selected bispectra for signal classification with application in radar target recognition
XD Zhang, Y Shi, Z Bao - IEEE Transactions on Signal …, 2001 - ieeexplore.ieee.org
Radially integrated bispectra (RIB), axially integrated bispectra (AIB), and circularly
integrated bispectra (CIB) were used as feature vectors of signals, but many bispectra on …
integrated bispectra (CIB) were used as feature vectors of signals, but many bispectra on …
Efficient radar target recognition using the MUSIC algorithm and invariant features
KT Kim, DK Seo, HT Kim - IEEE Transactions on Antennas and …, 2002 - ieeexplore.ieee.org
An efficient technique is developed to recognize target type using one-dimensional range
profiles. The proposed technique utilizes the Multiple Signal Classification algorithm to …
profiles. The proposed technique utilizes the Multiple Signal Classification algorithm to …
[HTML][HTML] Discrete human activity recognition and fall detection by combining FMCW RADAR data of heterogeneous environments for independent assistive living
Human activity monitoring is essential for a variety of applications in many fields, particularly
healthcare. The goal of this research work is to develop a system that can effectively detect …
healthcare. The goal of this research work is to develop a system that can effectively detect …
Joint time-frequency analysis for radar signal and image processing
VC Chen, H Ling - IEEE Signal Processing Magazine, 1999 - ieeexplore.ieee.org
The Fourier transform has been widely used in radar signal and image processing. When
the radar signals exhibit time-or frequency-varying behavior, an analysis that can represent …
the radar signals exhibit time-or frequency-varying behavior, an analysis that can represent …