Accurate detection and localization of unmanned aerial vehicle swarms-enabled mobile edge computing system
Unmanned aerial vehicle (UAV) swarms-enabled mobile edge computing system can be
deployed in critical industrial zones for monitoring. Meanwhile, its malicious use may bring …
deployed in critical industrial zones for monitoring. Meanwhile, its malicious use may bring …
Maneuvering target detection via Radon-fractional Fourier transform-based long-time coherent integration
X Chen, J Guan, N Liu, Y He - IEEE transactions on signal …, 2014 - ieeexplore.ieee.org
Long-time coherent integration technique is one of the most important methods for the
improvement of radar detection ability of a weak maneuvering target, whereas the …
improvement of radar detection ability of a weak maneuvering target, whereas the …
Cubic phase function: A simple solution to polynomial phase signal analysis
This article provides an overview of the cubic phase function (CPF) as a tool proposed for
both parametric and nonparametric estimation of the frequency modulated (FM) and in …
both parametric and nonparametric estimation of the frequency modulated (FM) and in …
Long-time coherent integration for weak maneuvering target detection and high-order motion parameter estimation based on keystone transform
P Huang, G Liao, Z Yang, XG Xia… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
In the airborne or spaceborne radar applications, prolonging the coherent integration time is
one of the effective methods to improve the radar detection ability of a weak maneuvering …
one of the effective methods to improve the radar detection ability of a weak maneuvering …
An efficient strategy for accurate detection and localization of UAV swarms
Unmanned aerial vehicle (UAV) swarms have shown great potential for Internet of Things
(IoT). Meantime, its malicious use may cause huge threat to the national security. UAV …
(IoT). Meantime, its malicious use may cause huge threat to the national security. UAV …
Coherent integration algorithm for a maneuvering target with high-order range migration
This paper considers the coherent integration problem for a maneuvering target with
complex motions, where the velocity, acceleration, and jerk result in respectively the first …
complex motions, where the velocity, acceleration, and jerk result in respectively the first …
Radar high-speed target detection based on the scaled inverse Fourier transform
J Zheng, T Su, W Zhu, X He… - IEEE Journal of Selected …, 2014 - ieeexplore.ieee.org
In this paper, by employing the symmetric autocorrelation function and the scaled inverse
Fourier transform (SCIFT), a coherent detection algorithm is proposed for high-speed …
Fourier transform (SCIFT), a coherent detection algorithm is proposed for high-speed …
Detection of weak maneuvering target based on keystone transform and matched filtering process
Detection of weak maneuvering target often suffers from the problems of the range migration
(RM) and the Doppler frequency migration (DFM) within the coherent pulse interval. In order …
(RM) and the Doppler frequency migration (DFM) within the coherent pulse interval. In order …
A fast SAR imaging method for ground moving target using a second-order WVD transform
P Huang, G Liao, Z Yang, XG Xia… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
In synthetic aperture radar (SAR) imaging of a ground moving target, long-time coherent
integration may effectively improve the imaging quality, whereas the imaging performance …
integration may effectively improve the imaging quality, whereas the imaging performance …
Ground maneuvering target imaging and high-order motion parameter estimation based on second-order keystone and generalized Hough-HAF transform
P Huang, G Liao, Z Yang, XG Xia… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
This paper proposes a new method to focus a ground moving target with complex motions
and estimate its motion parameters in a synthetic aperture radar (SAR) system. In this …
and estimate its motion parameters in a synthetic aperture radar (SAR) system. In this …