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基于改进OMP的非正侧视MIMO-STAP 算法 被引量:1

An Non-side-looking MIMO-STAP Algorithm Based on Improved OMP
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摘要 针对机载多输入多输出(MIMO)雷达空时自适应处理(STAP)技术在非正侧视条件下杂波抑制性能严重下降的问题,提出改进的正交匹配追踪算法(OMP)用于杂波谱的稀疏恢复。该算法首先确定非正侧视条件下的杂波脊线;然后在OMP算法的基础上增加了一条原子挑选依据,即原子对应点与杂波脊线的距离大小;不断挑选原子进入支撑集,直到残差小于门限值。仿真实验表明,使用OMP改进算法恢复出的杂波谱精度较高,得到的空时二维滤波器杂波抑制性能良好。 Aiming at the problem that the performance of airborne multi-input multi-output(MIMO)radar space-time adaptive processing(STAP)technology was seriously degraded under the condition of non-side-looking view,an improved OMP algorithm was proposed to recover the clutter spectrum.The algorithm firstly determined the clutter ridge line of non-side-looking view,then an atomic selection basis was added to OMP algorithm,that was,the distance between the corresponding point and the clutter ridge.Atoms were selected continuously into the support set until the residual was less than the threshold value.The simulation results showed that the improved OMP algorithm could recover the clutter spectrum with high accuracy and the obtained spatial-temporal filter had good clutter suppression performance.
作者 何团 唐波 张进 张玉 HE Tuan;TANG Bo;ZHANG Jin;ZHANG Yu(Electronic Countermeasure Institute,National University of Defense Technology,Hefei 230037,China)
出处 《探测与控制学报》 CSCD 北大核心 2019年第5期41-46,共6页 Journal of Detection & Control
基金 国家自然科学基金项目资助(61671453) 安徽省自然科学基金项目资助(1608085MF123)
关键词 多输入多输出 空时自适应处理 非正侧视 正交匹配追踪算法 稀疏恢复 multiple-input multiple-output(MIMO) space-time adaptive processing(STAP) non-side-looking OMP sparse recovery
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  • 1保铮,张庆文.一种新型的米波雷达──综合脉冲与孔径雷达[J].现代雷达,1995,17(1):1-13. 被引量:57
  • 2Klemm R. Space-time Adaptive Processing in Principles and Appfications [M]. London: IEE, 2002.65 - 75.
  • 3Reed I S,Mallett J D,Brennan L E. Rapid convergence rate in adaptive arrays [ J]. 1F.F.E Transactions on Aerospace and Elec- tronic Systems, 1974,10(6 ) :853 - 863.
  • 4SUN Ke, ZHANG Hao, LI Gang, MENG Hua-dong, WANG Xi-qin. A novel STAP algorithm using sparse recovery tech- nique [ A ]. IEEE International Conference on Geoscieuce & Remote Sensing Symposium [C]. Cape Town: IEEE, 2009. 336 - 339.
  • 5Donoho D L, Elad M, Temlyakov V N. Stable recovery of sparse overcomplete representations in the presence of noise[ J]. IEEE Transactions on Information Theory,2006,52( 1 ) : 6 - 18.
  • 6Boyd S P. Matlab Software for Disciplined Convex Program- ming [ CP]. http://www, stanford, edu/~ boyd/cvx, 2010.
  • 7Titi G W,Marshall D F. The ARPA/NAVY mountaintop pro- gram: adaptive signal processing for airborne early warning radar [ A]. 1EEE International Conference on Acoustics, Speech and Signal Processing [ C]. Atlanta: 1EF.E, 1996.1165 - 1168.
  • 8Krim H, Viberg M. Two decades of array signal processing re- search: the parametric approach [ J ]. IEEE Signal Processing Magazine, 1996,13(4) :67 - 94.
  • 9E Fishler, et al. Performance of MIMO radar systems: Advantages of angular diversity [ Z ]. Conference Record of the 38th Asilomar Conference on Signals, Systems and Computers. 2004, ( 1 ) :305 -309.
  • 10E Fishier, et al. MIMO radar:An idea whose time has come[ A ]. Proceeding of the IEEE Radar Conference [ C ]. Philadelphia, PA,2004.71 - 78.

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