机载MIMO雷达两级降维杂波抑制方法

吕晖; 冯大政; 和洁; 向聪

doi:10.3724/SP.J.1146.2010.00704

机载MIMO雷达两级降维杂波抑制方法

doi: 10.3724/SP.J.1146.2010.00704

吕晖^{* 冯大政和洁向聪,},
冯大政,
和洁,
向聪

基金项目:

国家自然科学基金(60971111)资助课题

计量
- 文章访问数: 3806
- HTML全文浏览量: 115
- PDF下载量: 1082
- 被引次数: 0
出版历程
- 收稿日期: 2010-07-06
- 修回日期: 2010-09-17
- 刊出日期: 2011-04-19

Two-stage Reduced-dimension Clutter Suppression Method for Airborne MIMO Radar

Lv Hui ^{* 冯大政和洁向聪
,},
Feng Da-Zheng,
He Jie,
Xiang Cong

摘要

摘要: 该文针对机载MIMO雷达杂波抑制问题，提出一种低复杂度的空时自适应处理 (STAP)方法。首先利用多普勒滤波对杂波信号进行时域降维处理；然后将空域发射-接收2维波束形成权向量表示成发射权和接收权的Kronecker积，并建立关于这两个权值的二元二次代价函数从而实现空域二次降维；最后提出最小化代价函数的双迭代算法，交替优化两个权值。仿真结果表明该算法收敛速度快，运算量小，尤其在小样本条件下其杂波抑制性能显著优于mDT方法。
- 机载雷达 /
- MIMO雷达 /
- 空时自适应处理 (STAP) /
- 杂波抑制 /
- 降维
Abstract: A computationally efficient Space-Time Adaptive Processing (STAP) method for clutter suppression in airborne MIMO radar is proposed. Firstly, the Doppler filtering is performed to reduce the data dimension in temporal domain. Secondly, the weight vector of the two-dimensional transmit-receive beamformer is expressed as the Kronecker product of two short weight vectors for which a bi-quadratic cost function is constructed to achieve dimension reduction in spatial domain. Finally, a bi-iterative algorithm for minimizing the bi-quadratic cost function is utilized to optimize iteratively the two weights. Simulation results indicate that the proposed method has fast convergence rate and particularly for short data records, it provides substantially better clutter suppression performance and can be carried out at a smaller computational cost than the mDT method.
- Airborne radar /
- MIMO radar /
- Space-Time Adaptive Processing (STAP) /
- Clutter suppression /
- Dimension reduction

HTML全文

参考文献(1)

Brennan L E and Reed I S. Theory of adaptive radar[J]. IEEE Transactions on Aerospace and Electronic Systems, 1973, 9(2): 237-252.[2] Bliss D W and Forsythe K W. Multiple-input multiple- output (MIMO) radar and imaging: degrees of freedom and resolution[C]. Proceedings of the 37th IEEE Asilomar Conference on Signals, Systems, Computers, Monterey, USA, 2003: 54-59.[3] Chen C Y and Vaidyanathan P P. MIMO radar space-time adaptive processing using prolate spheroidal wave functions[J]. IEEE Transactions on Signal Processing, 2008, 56(2): 623-635.[4] Mecca V F, Ramakrishnan D, and Krolik J L. MIMO radar space-time adaptive processing for multipath clutter mitigation[C]. Proceedings of the 4th IEEE Workshop on Sensor Array and Multichannel Signal Processing, Waltham, USA, 2006: 249-253.[5] Wang G H and Lu Y L. Clutter rank of MIMO radar with a special class of waveforms[C]. Proceedings of the International Waveform Diversity Design Conference, Kissimmee, USA, 2009: 108-112.[6] Marcos S. Range recursive space time adaptive processing (STAP) for MIMO airborne radar[C]. Proceedings of the 17th European Signal Processing Conference, Glasgow, Scotland, 2009: 592-596.[7] 王鞠庭, 江胜利, 何劲, 等. 机载MIMO雷达广义最大似然检测器[J]. 电子与信息学报, 2009, 31(6): 1315-1318.Wang Ju-ting, Jiang Sheng-li, and He Jin, et al.. Generalized likelihood ratio detector for airborne MIMO radars[J]. Journal of Electronics Information Technology, 2009, 31(6): 1315-1318.[8] 陈金立, 顾红, 苏卫民. 一种双基地MIMO雷达快速多目标定位方法[J]. 电子与信息学报, 2009, 31(7): 1664-1668.Chen Jin-li , Gu Hong, and Su Wei-min. A method for fast multi-target localization in bistatic MIMO radar system[J]. Journal of Electronics Information Technology, 2009, 31(7): 1664-1668.[9] Bao Zheng, Wu Shun-jun, and Liao Gui-sheng, et al.. Review of reduced rank space-time adaptive processing for airborne radars[C]. Proceedings of the International Conference on Radar, Beijing, China, 1996: 766-769.[10] Dippetro R C. Extended factored space-time processing forairborne radar system[C]. Proceedings of the 26th IEEE Asilomar Conference on Signals, Systems and Computers, Monterey, USA, 1992: 425-430.[11] 王永良, 彭应宁. 空时自适应信号处理 [M]. 北京: 清华大学出版社, 2000: 58-62.[12] Reed I S, Mallett J D, and Brennan L E. Rapid convergence rate in adaptive arrays[J]. IEEE Transactions on Aerospace and Electronic Systems, 1974, 10(6): 853-863.[13] Stoica P and Seln Y. Cyclic minimizers, majorization techniques, and expectation-maximization algorithm: a refresher[J]. IEEE Signal Processing Magazine, 2004, 21(1): 112-114.[14] Liu B, He Z S, Zeng J K, and Liu B Y. Polyphase orthogonal code design for MIMO radar systems[C]. Proceedings of the International conference on radar, Shanghai, China, 2006: 113-116.

施引文献

资源附件(0)

访问统计