In this paper, a reduced-rank angular parameters estimation algorithm is proposed for incoherently distributed (ID) noncircular sources based on a uniform linear array (ULA), which addresses the problems of central direction-of-arrival (DOA) estimation and angular spread estimation. Firstly, the noncircularity property of the signals is utilized to establish an extended generalized array manifold (GAM) model based on the first-order Taylor series approximation. Then, the central DOAs of source signals are obtained based on the generalized shift invariance property of the array manifold and the reduced-rank principle. Next, the angular spreads are estimated from the central moments of the angular distribution. Compared with the existing algorithm without exploiting the noncircularity information, the proposed one can achieve a higher accuracy and handle more sources. In addition, it can deal with a general scenario where different sources have different angular distribution shapes. Furthermore, the approximate stochastic Cramer-Rao bound (CRB) of the concerned problem is derived. Simulation results are provided to demonstrate the performance of the proposed algorithm.

提出了基于均匀线性阵列（ULA）的非相干分布（ID）非圆形源降秩角参数估计算法，解决了中心到达方向（DOA）估计和角展度问题。估计。首先，利用信号的非圆度特性，基于一阶泰勒级数逼近建立扩展的广义阵列流形（GAM）模型。然后，基于阵列流形的广义位移不变性和降秩原理，获得源信号的中心DOA。接下来，从角分布的中心矩估计角展度。与不利用非圆度信息的现有算法相比，建议的方法可以达到更高的精度并处理更多的源。另外，它可以处理一般情况，其中不同的源具有不同的角度分布形状。此外，得出了相关问题的近似随机克雷默-拉奥边界（CRB）。仿真结果表明了该算法的性能。