A Novel STAP Algorithm Based on Azimuth-Elevation Spectrum of Clutter
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| Xuất bản năm: | IET Conference Proceedings (Oct 14, 2015) |
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| Tác giả khác: | , |
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The Institution of Engineering & Technology
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| Những chủ đề: | |
| Truy cập trực tuyến: | Citation/Abstract Full Text - PDF |
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| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 1809799148 | ||
| 003 | UK-CbPIL | ||
| 020 | |a 978-1-78561-038-7 | ||
| 024 | 7 | |a 10.1049/cp.2015.0970 |2 doi | |
| 035 | |a 1809799148 | ||
| 045 | 0 | |b d20151014 | |
| 084 | |a 186328 |2 nlm | ||
| 100 | 1 | |a Feng, W K |u Air Force Eng. Univ., Xi'an, China | |
| 245 | 1 | |a A Novel STAP Algorithm Based on Azimuth-Elevation Spectrum of Clutter | |
| 260 | |b The Institution of Engineering & Technology |c Oct 14, 2015 | ||
| 513 | |a Conference Proceedings | ||
| 520 | 3 | |a The conception of clutter azimuth-elevation (AE) spectrum is brought forward, based on which a novel space-time adaptive processing (STAP) algorithm called AE based STAP (AE-STAP) algorithm is proposed in this paper. Instead of using clutter spatial-temporal spectrum for sparse recovery typed STAP algorithms and maximum likelihood estimation for statistic based STAP algorithms, the proposed algorithm utilizes the clutter AE spectrum, which is obtained by the sparse recovery technique and an elevation filter, to estimate the clutter covariance matrix and design the adaptive filter to suppress clutter. The proposed algorithm could achieve a greatly accurate estimation of clutter covariance matrix with few training samples, as well as avoid the influence of range ambiguous clutter and most false values appearing in the process of sparse recovery, and thus enjoy a great performance of clutter suppression and slowly moving targets detection. Simulation results are provided to illustrate the effectiveness of the proposed algorithm. | |
| 653 | |a Covariance matrix | ||
| 653 | |a Elevation | ||
| 653 | |a Economic models | ||
| 653 | |a Moving targets | ||
| 653 | |a Target detection | ||
| 653 | |a Recovery | ||
| 653 | |a Statistical methods | ||
| 653 | |a Maximum likelihood estimation | ||
| 653 | |a Clutter | ||
| 653 | |a Algorithms | ||
| 653 | |a Azimuth | ||
| 653 | |a Adaptive filters | ||
| 653 | |a Statistical analysis | ||
| 653 | |a Computer simulation | ||
| 653 | |a Adaptive algorithms | ||
| 653 | |a Space-time adaptive processing | ||
| 700 | 1 | |a Zhang, Y S |u Air Force Eng. Univ., Xi'an, China | |
| 700 | 1 | |a He, X Y |u Air Force Eng. Univ., Xi'an, China | |
| 773 | 0 | |t IET Conference Proceedings |g (Oct 14, 2015) | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/1809799148/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/1809799148/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |