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Coherent Signal DOA Estimation for MIMO Radar under Composite Background of Strong Interference and Non-Uniform Noise
by
Zheng, Guimei
, Zhou, Hao
, Lin, Bin
, Hu, Guoping
in
Accuracy
/ Algorithms
/ array signal processing
/ coherent signals
/ direction of arrival estimation
/ Eigenvalues
/ Eigenvectors
/ Localization
/ non-uniform noise
/ Radar systems
/ strong interference signals
2022
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Coherent Signal DOA Estimation for MIMO Radar under Composite Background of Strong Interference and Non-Uniform Noise
by
Zheng, Guimei
, Zhou, Hao
, Lin, Bin
, Hu, Guoping
in
Accuracy
/ Algorithms
/ array signal processing
/ coherent signals
/ direction of arrival estimation
/ Eigenvalues
/ Eigenvectors
/ Localization
/ non-uniform noise
/ Radar systems
/ strong interference signals
2022
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Do you wish to request the book?
Coherent Signal DOA Estimation for MIMO Radar under Composite Background of Strong Interference and Non-Uniform Noise
by
Zheng, Guimei
, Zhou, Hao
, Lin, Bin
, Hu, Guoping
in
Accuracy
/ Algorithms
/ array signal processing
/ coherent signals
/ direction of arrival estimation
/ Eigenvalues
/ Eigenvectors
/ Localization
/ non-uniform noise
/ Radar systems
/ strong interference signals
2022
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Coherent Signal DOA Estimation for MIMO Radar under Composite Background of Strong Interference and Non-Uniform Noise
Journal Article
Coherent Signal DOA Estimation for MIMO Radar under Composite Background of Strong Interference and Non-Uniform Noise
2022
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Overview
To address the problems of low accuracy and low robustness of the conventional algorithm in estimating the direction of arrival (DOA) of coherent signals against a composite background of strong interference and non-uniform noise, in this paper, a coherent signal DOA estimation algorithm based on fixed projection blocking is proposed in conjunction with a multi-input multi-output (MIMO) radar. The covariance matrix of the received signal is first decomposed by eigenvalues, and a fixed projection matrix orthogonal to the interference guidance vector is constructed as the interference blocking matrix. Then, the received array signal is pre-processed to re-form the covariance matrix, and this matrix is rendered decoherent through a Toeplitz reconstruction. Finally, the reconstructed covariance matrix is estimated by DOA using the propagation operator algorithm to reduce the complexity. The simulation verifies that the proposed algorithm has a better robustness and higher accuracy than conventional algorithms for the DOA estimation of coherent signals in composite backgrounds.
Publisher
MDPI AG,MDPI
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