Research on adaptive reduced-dimension STAP anti-interference based on multistage nested wiener filter

Wen Fei Gong; Xin Sun; Si Liang Wu

doi:10.3873/j.issn.1000-1328.2010.10.020

Research on adaptive reduced-dimension STAP anti-interference based on multistage nested wiener filter

Wen Fei Gong^*, Xin Sun, Si Liang Wu

^*Corresponding author for this work

School of Information and Electronics

Beijing Jiaotong University

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

An adaptive reduced-dimension space-time adaptive process (STAP) anti-interference method is proposed on the basis of analysis of the information of interference subspace and noise subspace provided by MSNWF. This method is used to analyze the varying trend of the cross-correlations between the adjacent desired signals in the forward interaction of MSNWF. Then optimal iterations are obtained by taking the information of interference subspace and noise subspace into account meanwhile. Thus optimal dimension can be adaptively selected without increasing the computational effort. Analysis and results of the experiment show that the proposed method further reduces the computational effort of STAP and enhances its real-time operation with the anti-interference performance unaffected.

Original language	English
Pages (from-to)	2360-2366
Number of pages	7
Journal	Yuhang Xuebao/Journal of Astronautics
Volume	31
Issue number	10
DOIs	https://doi.org/10.3873/j.issn.1000-1328.2010.10.020
Publication status	Published - Oct 2010

Keywords

Anti-interference
Interference subspace
Multistage nested Wiener filter (MSNWF)
Noise subspace
Reduced-dimension
Space-time adaptive process

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10.3873/j.issn.1000-1328.2010.10.020

Cite this

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title = "Research on adaptive reduced-dimension STAP anti-interference based on multistage nested wiener filter",

abstract = "An adaptive reduced-dimension space-time adaptive process (STAP) anti-interference method is proposed on the basis of analysis of the information of interference subspace and noise subspace provided by MSNWF. This method is used to analyze the varying trend of the cross-correlations between the adjacent desired signals in the forward interaction of MSNWF. Then optimal iterations are obtained by taking the information of interference subspace and noise subspace into account meanwhile. Thus optimal dimension can be adaptively selected without increasing the computational effort. Analysis and results of the experiment show that the proposed method further reduces the computational effort of STAP and enhances its real-time operation with the anti-interference performance unaffected.",

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AU - Gong, Wen Fei

AU - Sun, Xin

AU - Wu, Si Liang

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N2 - An adaptive reduced-dimension space-time adaptive process (STAP) anti-interference method is proposed on the basis of analysis of the information of interference subspace and noise subspace provided by MSNWF. This method is used to analyze the varying trend of the cross-correlations between the adjacent desired signals in the forward interaction of MSNWF. Then optimal iterations are obtained by taking the information of interference subspace and noise subspace into account meanwhile. Thus optimal dimension can be adaptively selected without increasing the computational effort. Analysis and results of the experiment show that the proposed method further reduces the computational effort of STAP and enhances its real-time operation with the anti-interference performance unaffected.

AB - An adaptive reduced-dimension space-time adaptive process (STAP) anti-interference method is proposed on the basis of analysis of the information of interference subspace and noise subspace provided by MSNWF. This method is used to analyze the varying trend of the cross-correlations between the adjacent desired signals in the forward interaction of MSNWF. Then optimal iterations are obtained by taking the information of interference subspace and noise subspace into account meanwhile. Thus optimal dimension can be adaptively selected without increasing the computational effort. Analysis and results of the experiment show that the proposed method further reduces the computational effort of STAP and enhances its real-time operation with the anti-interference performance unaffected.

KW - Anti-interference

KW - Interference subspace

KW - Multistage nested Wiener filter (MSNWF)

KW - Noise subspace

KW - Reduced-dimension

KW - Space-time adaptive process

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Research on adaptive reduced-dimension STAP anti-interference based on multistage nested wiener filter

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Keywords

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