摘要
针对L型阵列多输入多输出(multiple-input multiple-output,MIMO)雷达二维空间角估计问题,提出一种基于协方差矩阵联合稀疏重构的降维波达方向(direction of arrival,DOA)估计算法。该算法根据L型阵列MIMO雷达联合流型矢量的特点,通过降维矩阵的设计及回波数据的降维变换,最大程度地去除了所有的冗余数据;通过协方差矩阵联合构造稀疏线性模型,将2维角参量空间映射到1维空间,极大降低字典长度和求解复杂度的同时,不牺牲阵列孔径,实现了二维空间角度的有效估计和参数的自动配对。理论分析与实验仿真表明:与RD_MUSIC算法相比,本文降维处理有效提高阵元利用率的同时,最大程度地降低了回波数据的维数;与传统子空间类算法相比,基于协方差矩阵联合构造的稀疏线性模型充分利用了阵列孔径,无需预先估计目标数目,参数估计性能在低信噪比及小快拍数据长度下优势明显。最后,仿真结果验证了本文理论分析的正确性和算法的有效性。
Aiming at the problem of two dimensional angles estimation for multiple-input multiple-output （MIMO） radar with L-shaped array, a new reduced-dimensional direction of arrival （DOA） estimation method based on sparse reconstruction is proposed. Giving the steering vector of MIMO radar with L-shaped array, a reduced-dimensional matrix is employed, and data redundancy of high dimensional received data at the greatest degree can be removed via the reduced-dimensional transformation. Through the ioint construction of the two- dimensional sparse linear model with covariance matrix, the dimension of the dictionary is reduced to one-dimen- sion from two-dimensional space, and the length of the redundant dictionary and computation complexity is largely reduced. Furthermore, the method, without costing the aperture of array, can realize two dimensional spatial angles estimation with automatic pairing. Compared with reduced-dimensional （RD） MUSIC, the pro- posed method can reduce the dimension of received data at the greatest degree and enhance sensors efficiency. Com- pared with the traditional subspace algorithms, the proposed method, which is based on the joint sparse linear model of the covariance matrix, makes the best of all apertures of array and can achieve better estimation performance under lower signal-noise-ratio（SNR） and a few snapshots without pre-estimation for the number of targets. Finally, simula- tion results verify the correctness of the theoretical analysis and the effect of the proposed algorithm.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2015年第12期2725-2732,共8页
Systems Engineering and Electronics
基金
国家自然科学基金(60702015)资助课题
关键词
多输入多输出雷达
L型阵列
稀疏重构
波达方向估计
multiple-input multiple-output （MIMO） radar
L-shaped array
sparse reconstruction
direction of arrival （DOA） estimation
