基于 Hankel 矩阵分解的互素阵列高分辨目标定向

谭伟杰,冯西安,张杨梅

doi:10.13718/j.cnki.xdzk.2016.07.030

西南大学学报（自然科学版）

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基于 Hankel 矩阵分解的互素阵列高分辨目标定向

谭伟杰,冯西安,张杨梅. 基于 Hankel 矩阵分解的互素阵列高分辨目标定向[J]. 西南大学学报（自然科学版）, 2016, 38(7). doi: 10.13718/j.cnki.xdzk.2016.07.030

引用本文:

谭伟杰,冯西安,张杨梅. 基于 Hankel 矩阵分解的互素阵列高分辨目标定向[J]. 西南大学学报（自然科学版）, 2016, 38(7). doi: 10.13718/j.cnki.xdzk.2016.07.030

TAN Wei-jie,FENG Xi-an,ZHANG Yang-mei. High Resolution Target Direction Finding Based on Hankel Matrix Decomposition for Coprime Arrays[J]. Journal of Southwest University Natural Science Edition, 2016, 38(7). doi: 10.13718/j.cnki.xdzk.2016.07.030

Citation:

TAN Wei-jie,FENG Xi-an,ZHANG Yang-mei. High Resolution Target Direction Finding Based on Hankel Matrix Decomposition for Coprime Arrays[J]. Journal of Southwest University Natural Science Edition, 2016, 38(7). doi: 10.13718/j.cnki.xdzk.2016.07.030

基于 Hankel 矩阵分解的互素阵列高分辨目标定向

谭伟杰,冯西安,张杨梅

西北工业大学航海学院,西安,710072

High Resolution Target Direction Finding Based on Hankel Matrix Decomposition for Coprime Arrays

TAN Wei-jie,FENG Xi-an,ZHANG Yang-mei

摘要: 互素阵列能有效扩展阵列虚拟孔径，但预处理后的阵列模型为一确定噪声下的单快拍相干源目标方位估计问题。针对该问题，提出了一种基于 Hankel矩阵分解的方法，采用多项式求根的方法来进行高分辨定向。首先将阵列采样协方差数据进行Khatri‐Rao（KR）积预处理，进行相关数学变换后，用去冗余后的数据构建 Hankel矩阵，然后采用奇异值分解，转换为多项式求根，最后找出感兴趣的目标位置，并通过最小二乘法来求解出目标幅度。仿真结果表明了该方法的有效性和优越性。
- Hankel矩阵分解、互素阵列、网格失配、高分辨目标定向、近空间目标
Abstract: Co‐prime array has large virtual array aperture by Khatri‐Rao product processing ,but the array model after processing is equivalent to coherent sources estimation under determined noise on a single snapshot .In this paper ,a high resolution direction finding method based on decomposition of Hankel ma‐trices and polynomial rooting is proposed .First ,the covariance of the array data is preprocessed by KR product ,and repeated rows are removed through mathematical transformation .The obtained data is used to build a Hankel matrix .Then ,the problem is transformed into the determination of polynomial roots to find the interested target location through singular value decomposition on the Hankel matrix .Finally ,the amplitude of the target echo is solved by using the least squares method .To some extent ,the proposed method can overcome grid mismatch ,which is a problem in the traditional MUSIC method .Compared with the smoothing technology ,this method reduces the computational complexity and has good resolution even for a closely spaced target .Computer simulations verify the effectiveness and superiority of the new algorithm .
- Hankel matrix decomposition、co-prime array、grid mismatch、high resolution target direction finding、closely spaced target .

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基于 Hankel 矩阵分解的互素阵列高分辨目标定向

谭伟杰,冯西安,张杨梅

西北工业大学航海学院,西安,710072

关键词:

Hankel矩阵分解、互素阵列、网格失配、高分辨目标定向、近空间目标

摘要: 互素阵列能有效扩展阵列虚拟孔径，但预处理后的阵列模型为一确定噪声下的单快拍相干源目标方位估计问题。针对该问题，提出了一种基于 Hankel矩阵分解的方法，采用多项式求根的方法来进行高分辨定向。首先将阵列采样协方差数据进行Khatri‐Rao（KR）积预处理，进行相关数学变换后，用去冗余后的数据构建 Hankel矩阵，然后采用奇异值分解，转换为多项式求根，最后找出感兴趣的目标位置，并通过最小二乘法来求解出目标幅度。仿真结果表明了该方法的有效性和优越性。

English Abstract

High Resolution Target Direction Finding Based on Hankel Matrix Decomposition for Coprime Arrays

西北工业大学航海学院,西安,710072

Keywords:

Hankel矩阵分解、互素阵列、网格失配、高分辨目标定向、近空间目标

Abstract: Co‐prime array has large virtual array aperture by Khatri‐Rao product processing ,but the array model after processing is equivalent to coherent sources estimation under determined noise on a single snapshot .In this paper ,a high resolution direction finding method based on decomposition of Hankel ma‐trices and polynomial rooting is proposed .First ,the covariance of the array data is preprocessed by KR product ,and repeated rows are removed through mathematical transformation .The obtained data is used to build a Hankel matrix .Then ,the problem is transformed into the determination of polynomial roots to find the interested target location through singular value decomposition on the Hankel matrix .Finally ,the amplitude of the target echo is solved by using the least squares method .To some extent ,the proposed method can overcome grid mismatch ,which is a problem in the traditional MUSIC method .Compared with the smoothing technology ,this method reduces the computational complexity and has good resolution even for a closely spaced target .Computer simulations verify the effectiveness and superiority of the new algorithm .