Direct Data Domain Sparsity-Based STAP Utilizing Subaperture Smoothing Techniques
We propose a novel direct data domain (D3) sparsity-based space-time adaptive processing (STAP) algorithm utilizing subaperture smoothing techniques for airborne radar applications. Different from either normal sparsity-based STAP or D3 sparsity-based STAP, the proposed algorithm firstly uses only t...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2015/171808 |
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| author | Zhaocheng Yang Rui Fa Yuliang Qin Xiang Li Hongqiang Wang |
| author_facet | Zhaocheng Yang Rui Fa Yuliang Qin Xiang Li Hongqiang Wang |
| author_sort | Zhaocheng Yang |
| collection | DOAJ |
| description | We propose a novel direct data domain (D3) sparsity-based space-time adaptive processing (STAP) algorithm utilizing subaperture smoothing techniques for airborne radar applications. Different from either normal sparsity-based STAP or D3 sparsity-based STAP, the proposed algorithm firstly uses only the snapshot in the cell under test (CUT) to generate multiple subsnapshots by exploiting the space-time structure of the steering vector and the uncorrelated nature of the components of the interference covariance matrix. Since the interference spectrum is sparse in the whole angle-Doppler plane, by employing a sparse regularization, the generated multiple subsnapshots are jointly used to recover the interference spectrum. The interference covariance matrix is then estimated from the interference spectrum, followed by the space-time filtering and the target detection. Simulation results illustrate that the proposed algorithm outperforms the generalized forward/backward method, the conventional D3 least squares STAP algorithm, and the existing D3 sparsity-based STAP algorithm. Furthermore, compared with the normal sparsity-based STAP algorithm using multiple snapshots, the proposed algorithm can also avoid the performance degradation caused by discrete interferers merely appearing in the CUT. |
| format | Article |
| id | doaj-art-12ff15d8c78a42a2a83c8e7525817af9 |
| institution | Kabale University |
| issn | 1687-5869 1687-5877 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Antennas and Propagation |
| spelling | doaj-art-12ff15d8c78a42a2a83c8e7525817af92025-02-03T01:11:34ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772015-01-01201510.1155/2015/171808171808Direct Data Domain Sparsity-Based STAP Utilizing Subaperture Smoothing TechniquesZhaocheng Yang0Rui Fa1Yuliang Qin2Xiang Li3Hongqiang Wang4Research Institute of Space Electronics, Electronics Science and Engineering School, National University of Defense Technology, Changsha 410073, ChinaDepartment of Electrical Engineering and Electronics, The University of Liverpool, Liverpool L69 3GJ, UKResearch Institute of Space Electronics, Electronics Science and Engineering School, National University of Defense Technology, Changsha 410073, ChinaResearch Institute of Space Electronics, Electronics Science and Engineering School, National University of Defense Technology, Changsha 410073, ChinaResearch Institute of Space Electronics, Electronics Science and Engineering School, National University of Defense Technology, Changsha 410073, ChinaWe propose a novel direct data domain (D3) sparsity-based space-time adaptive processing (STAP) algorithm utilizing subaperture smoothing techniques for airborne radar applications. Different from either normal sparsity-based STAP or D3 sparsity-based STAP, the proposed algorithm firstly uses only the snapshot in the cell under test (CUT) to generate multiple subsnapshots by exploiting the space-time structure of the steering vector and the uncorrelated nature of the components of the interference covariance matrix. Since the interference spectrum is sparse in the whole angle-Doppler plane, by employing a sparse regularization, the generated multiple subsnapshots are jointly used to recover the interference spectrum. The interference covariance matrix is then estimated from the interference spectrum, followed by the space-time filtering and the target detection. Simulation results illustrate that the proposed algorithm outperforms the generalized forward/backward method, the conventional D3 least squares STAP algorithm, and the existing D3 sparsity-based STAP algorithm. Furthermore, compared with the normal sparsity-based STAP algorithm using multiple snapshots, the proposed algorithm can also avoid the performance degradation caused by discrete interferers merely appearing in the CUT.http://dx.doi.org/10.1155/2015/171808 |
| spellingShingle | Zhaocheng Yang Rui Fa Yuliang Qin Xiang Li Hongqiang Wang Direct Data Domain Sparsity-Based STAP Utilizing Subaperture Smoothing Techniques International Journal of Antennas and Propagation |
| title | Direct Data Domain Sparsity-Based STAP Utilizing Subaperture Smoothing Techniques |
| title_full | Direct Data Domain Sparsity-Based STAP Utilizing Subaperture Smoothing Techniques |
| title_fullStr | Direct Data Domain Sparsity-Based STAP Utilizing Subaperture Smoothing Techniques |
| title_full_unstemmed | Direct Data Domain Sparsity-Based STAP Utilizing Subaperture Smoothing Techniques |
| title_short | Direct Data Domain Sparsity-Based STAP Utilizing Subaperture Smoothing Techniques |
| title_sort | direct data domain sparsity based stap utilizing subaperture smoothing techniques |
| url | http://dx.doi.org/10.1155/2015/171808 |
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