Subspace extension algorithm for 2D DOA estimation with L-shaped sparse array
Subspace extension algorithm for 2D DOA estimation with L-shaped sparse array
复制标题
L型稀疏阵列二维DOA估计的子空间扩展算法
DOI：
10.1007/s11045-016-0406-3
复制
发表时间：
2017-01-01
影响因子：
2.5
通讯作者：
Cao, Hailin
中科院分区：
文献类型：
--
作者：
Liu, Sheng;Yang, Lisheng;Cao, Hailin
提出了一种L形阵二维波达方向估计的子空间扩展算法。该L形阵列由两个正交稀疏线性阵列（SLA）组成。每个SLA由两个不同的均匀线性阵列组成。该方法利用接收数据的互相关矩阵构造两个扩展信号子空间，分别估计方位角和仰角。扩展信号子空间的过程只需要很小的计算量。然后，提出了一种有效的配对方法来配对估计的仰角和方位角。虽然扩展了信号子空间，但算法的复杂度低于许多同类算法。仿真结果表明了所提出的配对匹配方法和子空间扩展算法的有效性。
A subspace extension algorithm for two-dimensional (2D) direction-of-arrival (DOA) estimation with an L-shaped array is proposed. This L-shaped array is comprised of two orthogonal sparse linear arrays (SLAs). Each SLA consists of two different uniform linear arrays. The cross-correlation matrix of received data is used to construct two extended signal subspaces, by which the azimuth angles and elevation angles can be estimated independently. The procedure used to extend signal subspace only needs a small amount of calculation. Then, an effective pair-matching method is addressed to pair the estimated elevation angles and azimuth angles. Although the signal subspaces are extended, the complexity of the proposed 2D DOA estimation algorithm is lower than many similar algorithms. Simulation results indicate the availability of the proposed pairing-matching method and subspace extension algorithm.