NDLI: Clutter nulling space-time adaptive processing algorithm based on sparse representation for airborne radar

Content Provider	IET Digital Library
Author	Zetao, Wang Yongliang, Wang Fei, Gao Keqing, Duan
Abstract	Traditional clutter subspace estimation algorithms try to solve the problem by estimating the clutter subspace eigenvectors from training samples, which are inevitably contaminated by noise. Actually, this can never be the best estimate, especially when the size of the training set is small. Furthermore, the omnipresent noise precludes the seeking of a pure clutter subspace. To cope with above drawbacks, the authors appeal to the sparse representation/recovery technique. From a mathematical viewpoint, the pure clutter subspace is spanned by the space-time steering vectors corresponding to the clutter component, and it can be constructed by a suitable set of space-time steering vectors selected from an overcomplete space-time steering dictionary. A criterion for selecting these space-time steering vectors is devised. Moreover, a clutter nulling type space-time adaptive processing algorithm is derived based on the proposed criterion. The resulting algorithm only needs the knowledge of the noise power rather than the clutter rank, which is quite troublesome to estimate in practice. Numerical results with both simulated and the Mountain-Top data demonstrate that the proposed algorithm has superior clutter suppression performance even with limited training samples.
Starting Page	177
Ending Page	184
Page Count	8
ISSN	17518784
Volume Number	11
e-ISSN	17518792
Issue Number	Issue 1, Jan (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rsn/11/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2016.0118
Journal	IET Radar, Sonar & Navigation
Publisher Date	2016-06-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Airborne Radar Clutter Nulling Space Time Adaptive Processing Algorithm Clutter Subspace Eigenvectors Clutter Subspace Estimation Algorithm Compressed Sensing Eigen Values And Eigen Function Electromagnetic Compatibility Estimation Theory Interference Interference Suppression Radar Clutter Radar Equipment Radar Theory Signal Processing And Detection Signal Representation Space Time Steering Vector Sparse Recovery Technique Sparse Representation Statistics System And Application
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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