Robust space-time adaptive processing based on covariance matrix reconstruction and steering vector correction
Clutter presents considerable heterogeneity in forward-looking airborne radar (FLAR) applications and conventional space-time adaptive processing (STAP) methods are sensitive to model mismatch. As a result, when a strong target signal contaminates the training samples, despite the use of guard cells...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-09-01
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| Series: | The Journal of Engineering |
| Subjects: | |
| Online Access: | https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0708 |
| _version_ | 1819291315503890432 |
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| author | Xueyao Hu Xinyu Zhang Yang Li Hongyu Wang Yanhua Wang |
| author_facet | Xueyao Hu Xinyu Zhang Yang Li Hongyu Wang Yanhua Wang |
| author_sort | Xueyao Hu |
| collection | DOAJ |
| description | Clutter presents considerable heterogeneity in forward-looking airborne radar (FLAR) applications and conventional space-time adaptive processing (STAP) methods are sensitive to model mismatch. As a result, when a strong target signal contaminates the training samples, despite the use of guard cells, the performance of conventional STAP methods degrades significantly. In this study, a robust method, which involves reconstructing a target-free covariance matrix and correcting the presumed steering vector to prevent target cancellation in FLAR, is proposed. First, the target-free covariance matrix is reconstructed through integrating the spatial–temporal spectrum over a sector separated from the desired frequency and direction of targets. Subsequently, the mismatch between presumed steering vector and actual steering vector is corrected via quadratic optimisation. In addition, the processing scheme is applied to real-measured clutter data, and the experimental results validate the effectiveness of the proposed method. |
| first_indexed | 2024-12-24T03:36:41Z |
| format | Article |
| id | doaj.art-8090c65691dd4cdaa12432ff703d58d6 |
| institution | Directory Open Access Journal |
| issn | 2051-3305 |
| language | English |
| last_indexed | 2024-12-24T03:36:41Z |
| publishDate | 2019-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Journal of Engineering |
| spelling | doaj.art-8090c65691dd4cdaa12432ff703d58d62022-12-21T17:17:02ZengWileyThe Journal of Engineering2051-33052019-09-0110.1049/joe.2019.0708JOE.2019.0708Robust space-time adaptive processing based on covariance matrix reconstruction and steering vector correctionXueyao Hu0Xinyu Zhang1Yang Li2Hongyu Wang3Yanhua Wang4Beijing Institute of TechnologyNational University of Defence TechnologyBeijing Institute of TechnologyBeijing Institute of TechnologyBeijing Institute of TechnologyClutter presents considerable heterogeneity in forward-looking airborne radar (FLAR) applications and conventional space-time adaptive processing (STAP) methods are sensitive to model mismatch. As a result, when a strong target signal contaminates the training samples, despite the use of guard cells, the performance of conventional STAP methods degrades significantly. In this study, a robust method, which involves reconstructing a target-free covariance matrix and correcting the presumed steering vector to prevent target cancellation in FLAR, is proposed. First, the target-free covariance matrix is reconstructed through integrating the spatial–temporal spectrum over a sector separated from the desired frequency and direction of targets. Subsequently, the mismatch between presumed steering vector and actual steering vector is corrected via quadratic optimisation. In addition, the processing scheme is applied to real-measured clutter data, and the experimental results validate the effectiveness of the proposed method.https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0708covariance matricesspace-time adaptive processingarray signal processingradar signal processingairborne radarradar clutterradar detectionconventional space-time adaptive processing methodsstrong target signalconventional stap methods degradesrobust methodtarget-free covariance matrixpresumed steering vectortarget cancellationflaractual steering vectorprocessing schemerobust space-time adaptive processingcovariance matrix reconstructionsteering vector correctionconsiderable heterogeneityairborne radar applications |
| spellingShingle | Xueyao Hu Xinyu Zhang Yang Li Hongyu Wang Yanhua Wang Robust space-time adaptive processing based on covariance matrix reconstruction and steering vector correction The Journal of Engineering covariance matrices space-time adaptive processing array signal processing radar signal processing airborne radar radar clutter radar detection conventional space-time adaptive processing methods strong target signal conventional stap methods degrades robust method target-free covariance matrix presumed steering vector target cancellation flar actual steering vector processing scheme robust space-time adaptive processing covariance matrix reconstruction steering vector correction considerable heterogeneity airborne radar applications |
| title | Robust space-time adaptive processing based on covariance matrix reconstruction and steering vector correction |
| title_full | Robust space-time adaptive processing based on covariance matrix reconstruction and steering vector correction |
| title_fullStr | Robust space-time adaptive processing based on covariance matrix reconstruction and steering vector correction |
| title_full_unstemmed | Robust space-time adaptive processing based on covariance matrix reconstruction and steering vector correction |
| title_short | Robust space-time adaptive processing based on covariance matrix reconstruction and steering vector correction |
| title_sort | robust space time adaptive processing based on covariance matrix reconstruction and steering vector correction |
| topic | covariance matrices space-time adaptive processing array signal processing radar signal processing airborne radar radar clutter radar detection conventional space-time adaptive processing methods strong target signal conventional stap methods degrades robust method target-free covariance matrix presumed steering vector target cancellation flar actual steering vector processing scheme robust space-time adaptive processing covariance matrix reconstruction steering vector correction considerable heterogeneity airborne radar applications |
| url | https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0708 |
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