稀疏空域融合DOA估计算法与性能分析

发布时间：2018-01-16 09:10

本文关键词：稀疏空域融合DOA估计算法与性能分析　出处：《现代雷达》2017年11期 　论文类型：期刊论文

【摘要】：压缩感知处理波达方向(DOA)估计问题中,阵列流型的构建是后续估计的基础。该文首先对阵列流型相邻导向矢量的正交性进行理论分析,分析表明在法线方向,等角划分优于等弦划分,在端射方向,等弦划分优于等角划分,相应的DOA估计性能更优。然后,系统推导出等弦划分与等角划分的临界值,并讨论阵元数、划分份数对正交性的影响,设计了一种优化稀疏划分模型,并提出了一种基于等弦和等角空间稀疏相结合的稀疏空域融合(SFSD)DOA估计算法。该算法较等弦划分和等角划分,具有更好的DOA估计稳健性、更低的信噪比门限和更高的估计精度。最后,通过仿真验证了模型的优越性和算法的高效性。
[Abstract]:The construction of array flow pattern is the basis of subsequent estimation in compressed sensing processing of DOA estimation. Firstly, the orthogonality of adjacent guidance vector of array flow pattern is analyzed theoretically. The analysis shows that isobaric partition is better than isoparic division in normal direction, and isometric division is better than isometric partition in endline direction. The corresponding DOA estimation performance is better. The critical values of equal-chord partitioning and isobaric partitioning are derived, and the effects of matrix number and partition number on orthogonality are discussed, and an optimized sparse partition model is designed. A sparse spatial fusion DOA DOA estimation algorithm based on equal-chord and isobaric space sparsity is proposed. The algorithm is more robust than the equal-chord partition and isobaric partition. Lower SNR threshold and higher estimation accuracy. Finally, the superiority of the model and the efficiency of the algorithm are verified by simulation.
【作者单位】：空军预警学院重点实验室;
【分类号】：TN911.7
【正文快照】： 0引言波达方向(DOA)估计一直以来都是阵列信号处理领域的一个热点问题,在雷达、导航、地震检测等众多领域有着广泛应用。MUSIC、MVM和MEM等经典的空间谱估计算法,均是建立在理想的阵列模型基础上的,所以算法的运用有着一些严格的条件,如不能适用于相干信号源、快拍数大于2~3倍

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