摘要
针对传统平行阵二维测向自由度低问题,提出一种改进型平行互素阵,基于稀疏表示方法和最小二乘法来估计目标方位。该方法首先利用改进型互素阵构建双平行稀疏阵列,计算平行互素阵的互协方差矩阵。然后通过矢量化处理,利用重排,去冗余处理生成较大孔径的虚拟阵列,将二维波达方向(direction of arrival,DOA)估计问题降维为一维DOA估计问题。进一步将一维DOA估计问题转为复数信号稀疏重构问题,并利用二阶锥规划来进行求解,通过峰值搜索得到方位角信息。最后利用方位角来构建方向矩阵,通过最小二乘方法求解俯仰角。该方法可以在没有目标先验信息的条件下,能够准确估计目标方位,且能够实现自动配对。相比传统的平行均匀线阵以及平行互素阵,该方法扩展了阵列虚拟孔径,提高了估计精度,能够辨识更多的目标源。实验仿真验证了该方法的有效性。
In order to improve the degree of freedom of the traditional parallel array, an improved two parallel co-prime array is proposed, an joint estimation method which combines sparse representation and least square method is utilized to estimate two-dimensional direction of arrival (DOA). Firstly, the cross-covariance matrix of the parallel co-prime array is constructed. Then, a virtual array with a large aperture is generated by vectori- zation , rearrangement and de-redundancy. Next, transform the two-dimensional DOA estimation problem to a one-dimensional DOA estimation problem. Furthermore, a sparse reconstruction problem of complex signals is formulated to estimate the azimuth, which is solved by second-order cone programming. Finally, the least square method is used to solve the elevation angle. This method can accurately estimate the azimuth and elevation of targets without the prior information of the target, and can achieve automatic pairing. Compared with the traditional parallel uniform linear array and the parallel co-prime array, the proposed array structure extends the virtual aperture of the array, improves the estimation accuracy and identifies more target sources. Simulation results demonstrate the effectiveness of the proposed method.
作者
谭伟杰
冯西安
TAN Weijie;FENG Xi’an(School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China)
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2019年第5期937-943,共7页
Systems Engineering and Electronics
基金
国家自然科学基金(61671378)资助课题
关键词
双平行阵
二维波达方向估计
稀疏表示
互素阵列
two parallel arrays
two-dimensional direction of arrival (DOA) estimation
sparse representation
co-prime array
