基于最小冗余线阵的二维DOA估计方法

针对传感器阵列二维DOA估计中阵元数较多且阵元利用率较低的问题,提出了一种低阵元冗余的二维DOA估计方法.该方法通过在最小冗余线阵基础上添加两个导向阵元的方法,将最小冗余线阵的应用拓展到二维DOA估计.同时该方法利用多个时延的阵元输出共轭循环相关函数构造"伪数据阵",在时空域中等效出两个具有旋转不变性的平行子阵,进而运用DOA矩阵法估计信号二维DOA.该方法不仅避免了最优时延选择问题,继承了DOA矩阵法无需谱峰搜索且无需二维角度参数配对等优点.还用较少的阵元获得了较大的阵列有效孔径.仿真结果表明,该方法与CCDM算法相比具有更好的低信噪比适应能力和稳健性.

Minimum-Redundancy Linear Array based Two-dimensional DOA Estimation Approach

To overcome the low sensor utilization rate problem existing in most two-dimensional (2-D) direction-of-arrival (DOA) estimation algorithms, a new method with low array redundancy is proposed in this paper. The proposed array configuration consists of a minimum redundancy linear array (MRLA) and two guiding sensors. With the help of these guiding sensors, the application of MRLA is extended to 2-D DOA estimation. Using multiple lag conjugate cyclic correlation functions of different sensor outputs, two pseudo-data matrices are constructed. Since the pseudo-data matrices can be regarded as the outputs of the two parallel arrays with rotational invariance property, the DOA Matrix idea is then applied to estimate the DOAs. The proposed method not only inherits the advantages of the DOA Matrix method, but also avoids the optimal lag choosing problem. Besides, this method obtains larger array aperture with fewer sensors. Simulation results verify that the proposed algorithm achieves better performance and better robustness than CCDM method.