基于最小特征值的近场源方位角和距离二维联合估计算法

Novel Algorithm of Joint Azimuth and Range Estimation for Near-Field Sources Based on the Smallest Eigenvalue

现有经典近场源参数估计方法一般基于线阵信号模型,利用线阵的特点处理,然而基于线阵的处理方法不能直接应用于圆阵。充分利用圆阵的对称性提出基于最小特征值的方位角和距离二维联合估计算法,对方向距离矢量进行矩阵分解,利用最小特征值先估计出方位角再估计距离,实现两个一维搜索代替复杂的二维谱峰搜索,无须参数配对,降低计算负担,提高算法的工程实用性。通过计算机仿真验证该算法的有效性。

Classical near-field sources processing algorithms are suited for line array since they use linear characteristics to estimate parameters.Though,they can not be directly applied to circle array.A novel method of joint azimuth and range estimation for near-field sources is proposed in this paper by the circle array symmetry,which decomposes direction-range vector.The smallest eigenvalue is used to estimate first the azimuth and then the range.Thus,the two-dimensional searching is replaced by the one-dimensional searching,with the parameters free of matching,the complicated operation reduced,and the practicability of algorithm improved.Effectiveness of the new algorithm is verified through computer simulations.