摘要
The problem of joint direction of arrival(DOA)and polarization estimation for polarization sensitive coprime planar arrays(PS-CPAs)is investigated,and a fast-convergence quadrilinear decomposition approach is proposed.Specifically,we first decompose the PS-CPA into two sparse polarization sensitive uniform planar subarrays and employ propagator method(PM)to construct the initial steering matrices separately.Then we arrange the received signals into two quadrilinear models so that the potential DOA and polarization estimates can be attained via quadrilinear alternating least square(QALS).Subsequently,we distinguish the true DOA estimates from the approximate intersecting estimations of the two subarrays in view of the coprime feature.Finally,the polarization estimates paired with DOA can be obtained.In contrast to the conventional QALS algorithm,the proposed approach can remarkably reduce the computational complexity without degrading the estimation performance.Simulations demonstrate the superiority of the proposed fast-convergence approach for PS-CPAs.
调查了极化面阵中的波达方向估计(Direction of arrival,DOA)与极化估计问题,并提出了一种快速收敛的四线性分解算法。具体来说,首先把互质面阵分解为两个均匀面阵并利用传播算子算法得到了初始的方向矩阵估计。然后,将接受信号置于四线性模型,利用四线性交替最小二乘来估计所有可能的DOA与极化估计结果。接着,根据互质解模糊的原理,从所有的结果中提取出真正的估计值,消除了模糊估计结果。对比于传统的四线性交替最小二乘算法,本算法可以在不损失估计性能的前提下,极大程度地降低复杂度。仿真结果证明了极化互质面阵下本快速收敛算法的优越性。
基金
supported by the Open Research Fund of the State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System(No.CEMEE2019Z0104B)。
