Results 31 to 40 of about 4,790 (193)

Knowledge‐aided block sparse Bayesian learning STAP for phased‐array MIMO airborne radar

IET Radar, Sonar & Navigation, 2021
The phased‐array multiple‐input multiple‐output (PA‐MIMO) airborne radar faces more severe sample shortage problem than the conventional PA radar. Hence, it suffers from severe performance degradation when it adopts the traditional space‐time adaptive ...
Ning Cui, Kun Xing, Keqing Duan, Zhongjun Yu   +3 more
doaj   +1 more source

A novel sparse recovery‐based space‐time adaptive processing algorithm based on gridless sparse Bayesian learning for non‐sidelooking airborne radar

IET Radar, Sonar & Navigation, 2023
Non‐sidelooking airborne radar encounters significant non‐stationary and heterogeneous clutter environments, resulting in a severe shortage of samples.
Weichen Cui, Tong Wang, Degen Wang, Xinying Zhang   +3 more
doaj   +1 more source

Joint phase error estimation and sparse scene restoration algorithms for frequency agile radar

IET Radar, Sonar & Navigation, 2021
Frequency agile radar (FAR) systems have been demonstrated to have outstanding performance in electronic counter‐countermeasures (ECCM). With increased bandwidth in which FAR can switch carrier frequency, the phase errorswill appear at the corresponding ...
Zhiting Fei, Jindong Zhang, Xiaohua Zhu, Xun Ding   +3 more
doaj   +1 more source

Deep Unfolding Based Space-Time Adaptive Processing Method for Airborne Radar

Leida xuebao, 2022
The Sparse Recovery Space-Time Adaptive Processing (SR-STAP) method can use a small number of training range cells to effectively suppress the clutter of airborne radar.
Hangui ZHU, Weike FENG, Cunqian FENG, Bo ZOU, Fuyu LU   +4 more
doaj   +1 more source

Spiking Sparse Recovery with Non-convex Penalties

, 2022
International audienceSparse recovery (SR) based on spiking neural networks has been shown to be computationally efficient with ultra-low power consumption.
Yu, Lei, Eldar, Yonina, C, Zhang, Xiang, Zheng, Gang   +3 more
core   +1 more source

Jointly Iterative Adaptive Approach Based Space Time Adaptive Processing Using MIMO Radar

IEEE Access, 2018
To solve the problem of large training samples requirement of space time adaptive processing (STAP), a jointly sparse matrices recovery-based method is proposed for clutter plus noise covariance matrix estimation by exploiting the transmitting waveform ...
Weike Feng, Yiduo Guo, Xingyu He, Hanwei Liu, Jian Gong   +4 more
doaj   +1 more source

Convolutional Sparse Support Estimator Network (CSEN): From Energy-Efficient Support Estimation to Learning-Aided Compressive Sensing

, 2021
<p>Support estimation (SE) of a sparse signal refers to finding the location indices of the nonzero elements in a sparse representation. Most of the traditional approaches dealing with SE problems are iterative algorithms based on greedy methods or
Ahishali, Mete, Kiranyaz, Serkan, Gabbouj, Moncef, Yamac, Mehmet   +3 more
core   +2 more sources

A fast and gridless STAP algorithm based on mixed‐norm minimisation and the alternating direction method of multipliers

IET Radar, Sonar & Navigation, 2021
Sparse recovery (SR) based space‐time adaptive processing (STAP) methods have received much attention recently due to their dramatically reduced requirements of training samples.
Zhongyue Li, Tong Wang, Yuyu Su
doaj   +1 more source

Maximal Dependence Capturing as a Principle of Sensory Processing

Frontiers in Computational Neuroscience, 2022
Sensory inputs conveying information about the environment are often noisy and incomplete, yet the brain can achieve remarkable consistency in recognizing objects.
Rishabh Raj, Dar Dahlen, Kyle Duyck, C. Ron Yu, C. Ron Yu   +4 more
doaj   +1 more source

A Dynamical System With Fixed Convergence Time for Sparse Recovery

IEEE Access, 2019
The sparse recovery (SR) algorithm, under the premise that signals are sparse, can be divided into two categories. One is a digital discrete method implemented via lots of iterative computations and the other is a continuous method implemented via analog
Junying Ren, Lei Yu, Yulun Jiang, Jean-Pierre Barbot, Hong Sun   +4 more
doaj   +1 more source