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  • 陈金立,郑瑶,李家强,叶树霞. 基于迭代近端投影的MIMO雷达多快拍DOA估计[J]. 雷达科学与技术, 2020, 18(1): 56-62.    [点击复制]
  • CHEN Jinli,ZHENG Yao,LI Jiaqiang,YE Shuxia. MIMO Radar DOA Estimation for Multiple Snapshots Based on Iterative Proximal Projection[J]. Radar Science and Technology, 2020, 18(1): 56-62.   [点击复制]
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基于迭代近端投影的MIMO雷达多快拍DOA估计
陈金立,郑瑶,李家强,叶树霞
0
(1.南京信息工程大学气象灾害预报预警与评估协同创新中心,江苏南京210044;2.南京信息工程大学电子与信息工程学院,江苏南京210044;3.江苏科技大学电子信息学院,江苏镇江212003)
摘要:
传统基于压缩感知的MIMO雷达DOA估计算法将非凸非平滑稀疏表示问题近似成凸或平滑函数问题进行求解,稀疏表示模型误差的存在导致DOA估计性能不理想。为此,提出了一种基于迭代近端投影的MIMO雷达多快拍DOA估计方法。该方法首先将高维回波数据转换至低维空间以降低空域维度,并对降维后的数据进行奇异值分解(Singular Value Decomposition,SVD),提取信号子空间以降低时域维度,利用近端函数优化模型来表示MIMO雷达多快拍DOA估计中的非凸非平滑稀疏表示问题,然后采用SCAD(Smoothly Clipped Absolute Deviation Penalty)函数获得近端算子以求解该模型。仿真结果表明,该方法在低快拍和低信噪比下相干信源的DOA估计性能优于现有算法。
关键词:  MIMO雷达  DOA估计  多快拍  迭代近端投影  SCAD阈值函数
DOI:DOI:10.3969/j.issn.1672-2337.2020.01.010
基金项目:国家自然科学基金(No.61302188,61372066,11304394);江苏省自然科学基金(No.BK20131005)
MIMO Radar DOA Estimation for Multiple Snapshots Based on Iterative Proximal Projection
CHEN Jinli,ZHENG Yao,LI Jiaqiang,YE Shuxia
(1. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science and Technology,Nanjing 210044,China;2. School of Electronics and Information Engineering,Nanjing University of Information Science and Technology,Nanjing 210044,China;3. School of Electronics and Information,Jiangsu University of Science and Technology,Zhenjiang 210044,China)
Abstract:
In the traditional DOA estimation algorithm for MIMO radar via compressed sensing,the problem of nonconvex and nonsmooth sparse representation is approximated as the convex or smooth function problem. However,the existence of sparse representation model error brings about poor DOA estimation performance.To this end,a method based on iterative proximal projection for MIMO radar DOA estimation with multiple snapshots is presented in this paper.The echo data with high spatial dimension is firstly compressed into a low spatial dimension data on which a singular value decomposition (SVD) is performed to extract signal subspace with reduced time dimension. Then,the optimization model based on proximal function is used for describing the nonconvex and nonsmooth sparse representation problem of MIMO radar DOA estimation with multiple snapshots. Finally,the proximity operator is obtained by the smoothly clipped absolute deviation penalty(SCAD)threshold function for solving that optimization problem.Simulation results show that the proposed algorithm can improve the coherent DOA estimation performance in the case of low signaltonoise ratio (SNR) with small number of snapshots compared with the existing algorithms.
Key words:  MIMO radar  DOA estimation  multiple snapshots  iterative proximal projection  SCAD threshold function