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Content Provider | IET Digital Library |
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Author | Duan, Keqing Xu, Hong Yuan, Huadong Xie, Wenchong Wang, Yongliang |
Abstract | Conventional 3-dimensional (3D) space-time adaptive processing (STAP) has achieved good performance for non-stationary clutter suppression. However, the performance of 3D STAP rapidly degrades when applied to heterogeneous clutter environment due to the requirement of a large number of independent and identically distributed training samples to estimate the clutter covariance matrix. This study applies an efficient sparse recovery algorithm, i.e. multiple sparse Bayesian learning (MSBL), with tuning, to solve the limited sample problem of 3D STAP in airborne radar. Differing with the conventional 2D sparsity-based STAP, the proposed method utilises the sparsity of clutter in elevation-azimuth-Doppler domain and recovers the 3D clutter spectrum. Whereas in its’ large computational load, a fast algorithm extending the relevance vector machine is also considered. |
Starting Page | 5478 |
Ending Page | 5482 |
Page Count | 5 |
Volume Number | 2019 |
e-ISSN | 20513305 |
Issue Number | Issue 19, Oct (2019) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/joe/2019/19 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0343 |
Journal | The Journal of Engineering |
Publisher | The Institution of Engineering and Technology |
Publisher Date | 2019-05-30 |
Access Restriction | Open |
Rights License | Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) |
Subject Keyword | 3-dimensional Space-time Adaptive Processing 3D Clutter Spectrum Airborne Radar Bayes Method Clutter Covariance Matrix Conventional 2D Sparsity-based STAP Covariance Matrices Dimensional Sparse Recovery Space-time Adaptive Processing Efficient Sparse Recovery Algorithm Heterogeneous Clutter Environment Identically Distributed Training Sample Independent Distributed Training Sample Knowledge Engineering Technique Learning in AI Multiple Sparse Bayesian Learning Nonstationary Clutter Suppression Optical, Image And Video Signal Processing Radar Clutter Radar Detection Radar Equipment Radar Signal Processing Radar Theory Signal Processing And Detection Space-time Adaptive Processing Statistics System And Application |
Content Type | Text |
Resource Type | Article |
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