Space-Time Adaptive Processing for Airborne Radars With Space-Time Coprime Sampling Structure
Space-Time Adaptive Processing for Airborne Radars With Space-Time Coprime Sampling Structure
复制标题
具有时空互质采样结构的机载雷达空时自适应处理
DOI：
10.1109/access.2018.2822046
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发表时间：
2018-04
期刊：
影响因子：
3.9
通讯作者：
Jiang Mei
中科院分区：
文献类型：
--
作者：
Wang Xiaoye;Yang Zhaocheng;Huang Huiping;Huang Jianjun;Jiang Mei
互质阵列和共质时间采样器由于具有大孔径和低成本可实现的自由度等优点，近年来受到人们的广泛关注。与传统的均匀发射脉冲的机载雷达不同，该雷达在接收端配置互质阵列，以互质的重复间隔发射脉冲。由于这种采样结构违反了传统杂波秩值估计准则的条件，本文首先提出了一种基于有效孔径带宽乘积的杂波秩值估计方法。然后，利用重建的虚拟时空快照，提出了两种空时自适应处理(STAP)算法，即样本矩阵逆算法和主成分自适应算法。此外，还对所提出的算法进行了深入的理论收敛分析。仿真结果验证了所提STAP算法的有效性。
Coprime arrays and coprime time samplers have been receiving attractive attention recently due to their advantages of large apertures and achievable degrees of freedom with low cost. In this paper, different from traditional airborne radar with uniform transmitting pulses, the considered radar is configured with a coprime array in receiver and transmits the pulses with coprime repetition intervals. Because this sampling structure violates the conditions of the conventional clutter rank estimation rules, we first propose a novel method to estimate the clutter rank based on effective aperture-bandwidth product. Then, two space-time adaptive processing (STAP) algorithms, namely, the sample matrix inverse- and principal components-STAP, are proposed by using the reconstructed virtual space-time snapshots. Additionally, a thoroughly theoretical convergence analysis of the proposed algorithms is conducted. Exclusive simulation results are provided to demonstrate the effectiveness of the proposed STAP algorithms.
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影响因子：
5.4
作者：
Zhaocheng Yang;R. D. Lamare;Xiang Li
通讯作者：
Zhaocheng Yang;R. D. Lamare;Xiang Li
DOI：
10.1109/acssc.1999.832013
发表时间：
1999-10
期刊：
Conference Record of the Thirty-Third Asilomar Conference on Signals, Systems, and Computers (Cat. No.CH37020)
影响因子：
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作者：
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通讯作者：
A. Sarajedini
DOI：
10.1109/acssc.1998.751584
发表时间：
1998-11
期刊：
Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284)
影响因子：
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作者：
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通讯作者：
J. Ward
DOI：
10.1109/radar.2016.8059244
发表时间：
2016-10
期刊：
2016 CIE International Conference on Radar (RADAR)
影响因子：
--
作者：
Yuanbin Ma;Zhaocheng Yang;Jingxiong Huang;Jianjun Huang;Li Kang
通讯作者：
Yuanbin Ma;Zhaocheng Yang;Jingxiong Huang;Jianjun Huang;Li Kang
DOI：
10.1109/radar.2017.7944297
发表时间：
2017-05
期刊：
2017 IEEE Radar Conference (RadarConf)
影响因子：
--
作者：
Ruiyang Li;Yikai Wang-;Zishu He;Jun Yu Li;Guohao Sun
通讯作者：
Ruiyang Li;Yikai Wang-;Zishu He;Jun Yu Li;Guohao Sun