.png){kind=icon}
Return
A Joint Sparse Space-Time Adaptive Processing Method
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2020.3001304.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
At present, most of the sparse space-time adaptive processing(STAP) methods focus on exploiting the clutter sparsity. In this paper, different from the present sparse STAP methods, both the clutter sparsity and the target sparsity in STAP are considered at the same time, and a novel joint sparse STAP method is proposed. The proposed method imposes a sparse regularization on the clutter and the target to the minimum Capon Spectrum criterion. The processing results of the measured data shows that the output SCNR of the proposed method is 3dB higher than the method proposed by Yang et al. and 2dB higher than the method proposed by Zhiqi et al.
Keywords:
Clutter
Covariance matrices
Sparse matrices
Radar detection
STAP
L-1-regularized
joint sparse
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.6
Papers:
9.8W
Citations:
29.4W
Organization
No organization information available
Cited Papers
Robust Constrained Inverse Beamforming Algorithm Based on Space Time Adaptive Processing.png)
IEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAIShareSaveAmyloid Fibrils of Pisum sativum L. Vicilin Inhibit Pathological Aggregation of Mammalian Proteins
OAAI
OAAIShareSaveRobust STAP Against Unknown Mutual Coupling Based on Middle Subarray Clutter Covariance Matrix ReconstructionIEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAIShareSaveSparse Representation Based Algorithm for Airborne Radar in Beam-Space Post-Doppler Reduced-Dimension Space-Time Adaptive ProcessingIEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAIShareSaveA Fast and Noise-Robust Algorithm for Joint Sparse Recovery Through Information TransferIEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAIShareSave
View more