A Fast IAA–Based SR–STAP Method for Airborne Radar
-д хадгалсан:
| -д хэвлэсэн: | Remote Sensing vol. 16, no. 8 (2024), p. 1388 |
|---|---|
| Үндсэн зохиолч: | |
| Бусад зохиолчид: | , , |
| Хэвлэсэн: |
MDPI AG
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| Нөхцлүүд: | |
| Онлайн хандалт: | Citation/Abstract Full Text + Graphics Full Text - PDF |
| Шошгууд: |
Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!
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MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3047079737 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2072-4292 | ||
| 024 | 7 | |a 10.3390/rs16081388 |2 doi | |
| 035 | |a 3047079737 | ||
| 045 | 2 | |b d20240101 |b d20241231 | |
| 084 | |a 231556 |2 nlm | ||
| 100 | 1 | |a Zhang, Shuguang | |
| 245 | 1 | |a A Fast IAA–Based SR–STAP Method for Airborne Radar | |
| 260 | |b MDPI AG |c 2024 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Space–time adaptive processing (STAP) is an effective technology in clutter suppression and moving target detection for airborne radar. When working in the heterogeneous environment, the number of training samples that satisfy independent and identically distributed (IID) conditions is insufficient, making it difficult to ensure the estimation accuracy of the clutter plus noise covariance matrix for traditional STAP methods. Sparse recovery–based STAP (SR–STAP) methods have received widespread attention in the past few years. The accurate estimation of the clutter plus noise covariance matrix can be achieved using only a few training samples. The iterative adaptive approach (IAA) can quickly and accurately estimate the power spectrum, but applying this method directly to the STAP method cannot produce good performance. In this paper, a fast IAA–based SR–STAP method is proposed. Based on the weighted <inline-formula>l1</inline-formula> problem, the IAA spectrum is used as a weighted term to obtain a good approximation. In order to obtain an analytical solution, we use the weighted <inline-formula>l2</inline-formula> norm to approximate the weighted <inline-formula>l1</inline-formula> norm without loss of performance. Compared with the IAA–STAP method, the proposed method is more robust to errors. Moreover, the proposed method has a fast computational speed. The effectiveness of the proposed method is demonstrated by simulations. | |
| 653 | |a Covariance matrix | ||
| 653 | |a Accuracy | ||
| 653 | |a Radar detection | ||
| 653 | |a Radar | ||
| 653 | |a Adaptive sampling | ||
| 653 | |a Maximum likelihood method | ||
| 653 | |a Moving targets | ||
| 653 | |a Target detection | ||
| 653 | |a Exact solutions | ||
| 653 | |a Clutter | ||
| 653 | |a Training | ||
| 653 | |a Airborne radar | ||
| 653 | |a Space-time adaptive processing | ||
| 653 | |a Radar systems | ||
| 700 | 1 | |a Wang, Tong | |
| 700 | 1 | |a Liu, Cheng | |
| 700 | 1 | |a Ren, Bing | |
| 773 | 0 | |t Remote Sensing |g vol. 16, no. 8 (2024), p. 1388 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3047079737/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3047079737/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3047079737/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |