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作 者:张晋 王大鸣[1] 崔维嘉[1] 巴斌 许海韵 Zhang Jin;Wang Daming;Cui Weijia;Ba Bin;Xu Haiyun(Institute of Information System Engineering,Information Engineering University,Zhengzhou 450001,China)
机构地区:[1]信息工程大学信息系统工程学院,郑州450001
出 处:《计算机应用研究》2021年第7期2060-2065,共6页Application Research of Computers
基 金:国家自然科学基金资助项目。
摘 要:针对现有大多数循环平稳信号DOA估计算法复杂度较高、估计精度低无法实现对有用信号的欠定估计问题,提出了一种基于互质阵的循环平稳信号低复杂度、欠定DOA估计算法。算法的主要思想是利用互质阵良好的稀疏特性,通过矢量化处理构造虚拟阵列模型,扩展阵列孔径,实现阵列自由度的提升。首先,算法构造了互质阵输出的循环自相关矩阵,然后进行矢量化处理得到最大连续虚拟阵元部分,给出其谱峰搜索的表达式。最后,为降低计算复杂度,对算法进行改进,应用多项式求根的方法直接求解DOA估计值。仿真结果表明,所提算法能实现对有用信号的欠定估计,计算复杂度较低,且相比于大多数的循环平稳信号DOA估计算法,所提算法估计自由度和估计精度有了进一步的提升。In view of the problems that most cyclostationary signals DOA estimation algorithms have high complexity,low accuracy,and disability to realize underdetermined estimation of useful signals,this paper proposed a low-complexity and underdetermined DOA estimation algorithm for cyclostationary signals based on a coprime array.The main idea of the proposed algorithm was to use the good sparse characteristics of the matrix to construct a virtual array model through vectorization processing.The proposed algorithm expanded the array aperture,and improved the degree of freedom.Firstly,the proposed algorithm constructed the cyclic autocorrelation matrix output by the coprime matrix,and then performed vectorization process to obtain the largest continuous virtual element part,and gave the expression of its spectral peak search.Finally,the improved algorithm used the method of polynomial to find the roots to directly solve the DOA estimation value,it greatly reduced the computational complexity.The simulation results show that the proposed algorithm can realize under-determined estimation of useful signals,and the computational complexity is low.Compared with most cyclostationary signals DOA estimation algorithms,the estimation degree of freedom and the estimation accuracy of the proposed algorithm are further improved.
分 类 号:TN911.7[电子电信—通信与信息系统]
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