多口径组合阵列子空间DOA测向算法

果然, 毛兴鹏, 李绍滨

(哈尔滨工业大学 电子与信息工程学院, 150001 哈尔滨)



摘要:

现有各类子空间DOA测向算法为避免阵列模糊一般要求阵元间距小于半波长,但为获得更好的测向性能又需要较大的阵列尺寸,这需要大量的阵元,提高系统复杂度和成本. 为克服这个问题,本文基于多重信号分类(MUSIC)算法提出一种采用半径不同的多口径组合阵列进行DOA测向方法. 其中小尺寸阵列能够避免测向模糊问题,同时对空间谱起到平滑作用,从而降低空间谱计算复杂度；而具有较少阵元数目的大尺寸阵列主要用于提高测向算法精度和分辨力. 本文给出算法的原理与实现步骤,并对算法精度和分辨力进行了分析和仿真,理论分析和仿真结果表明算法的有效性.

关键词:  信号波达方向测向  多重信号分类(MUSIC)算法  阵列模糊  组合孔径阵列

DOI：10.11918/j.issn.0367-6234.2015.03.003

分类号:TN958.3

基金项目:国家自然科学基金(61171180).



A novel DOA estimation algorithm based on combined arrays of various apertures

GUO Ran, MAO Xingpeng, LI Shaobin

(School of Information Engineering, Harbin Institute of Technology, 150001 Harbin, China)

Abstract:

Many of Current DOA estimation algorithms have to be exerted on arrays whose inter-antenna distance are less than half wavelength of the arrivals to avoid the ambiguity phenomenon. However, to acquire decent performance in accuracy and resolution, arrays of larger aperture have to be adopted, increases the number of sensors, and enhances the complexity of hardware and cost. To which solve these problems, this paper proposes an algorithm oriented from Multiple Signal Classification (MUSIC), which operates on an array combined of multiple arrays of different apertures. The subarray of smaller aperture helps to eliminate the ambiguity, smooth the spatial spectrum and reduce the calculation complexity, while the larger subarray improves the performance in accuracy and resolution. The principle and steps of the algorithms are presented, and a detailed performance analysis and simulation results are given, which verify the validity of this algorithm.

Key words:  direction of arrivals (DOA) estimation  multiple Signal Classification (MUSIC)  ambiguity of array  combined array of various apertures