在阵元数确定的情况下,稀疏互质阵列能增大阵列孔径.为利用阵列的互质关系形成具有更多自由度的互质差合成阵列,采用稀疏重构方法,提出一种迭代加权l1范数约束波达方向(DOA)估计算法.通过矢量化对稀疏互质阵列进行孔径扩展,进而在相应的过完备基下获得观测模型的l0范数约束稀疏重构,再用加权l1范数约束代替l0范数约束重构方法,采用多次迭代运算求取最优解实现DOA估计.实验结果表明,该算法能够更好地利用稀疏互质阵列的阵列孔径,提高测向精度,并且通过迭代运算来弥合l1范数约束与l0范数约束之间的差别,克服传统l1范数约束类算法存在估计偏差的缺点.%The sparse coprime array with determined elements can increase the array aperture.In order to make full use of the coprime relationship of the array to form differential coprime synthetic array with more degrees of freedom,this paper exploits the method of sparse reconstruction,and proposes a new Direction-of-Arrival(DOA) estimation algorithm based on iterative weighted l1 norm.The aperture of sparse coprime array can be increased by vectoring.The l0 norm of the observation model corresponding to the related overcomplete basis is successively obtained,and the l0 norm constraint is substituted by weighted l1 norm constraint for reconstruction.Multiple iterations are used to obtain the optimal solution to realize DOA estimation.Experimental results show that,compared with other algorithms,the proposed algorithm can effectively utilize the aperture of the sparse coprime array to improve the direction finding accuracy,and can reduce the gap between l1 norm and l0 norm by multiple iterations so that the shortcoming of conventional l1 norm constraint type algorithms can be overcome.
展开▼
