J4 ›› 2015, Vol. 42 ›› Issue (3): 122-128.doi: 10.3969/j.issn.1001-2400.2015.03.021

• 研究论文 • 上一篇    下一篇

一种未知信源数的共形阵DOA算法

杨群;曹祥玉;高军;李思佳   

  1. (空军工程大学 信息与导航学院,陕西 西安  710077)
  • 收稿日期:2014-04-22 出版日期:2015-06-20 发布日期:2015-07-27
  • 通讯作者: 杨群
  • 作者简介:杨群(1985-),男,空军工程大学博士研究生,E-mail: yangqunjyb@163.com.
  • 基金资助:

    国家自然科学基金资助项目(61271100,61471389);陕西省自然科学基金研究重点资助项目(2010JZ010);陕西省自然科学基金资助项目(2012JM8003)

Algorithm for conformal array DOA estimation with an unknown number of sources

YANG Qun;CAO Xiangyu;GAO Jun;LI Sijia   

  1. (Information and Navigation Institute, AFEU, Xi'an  710077, China)
  • Received:2014-04-22 Online:2015-06-20 Published:2015-07-27
  • Contact: YANG Qun

摘要:

针对目前绝大多数共形阵波达方向估计算法需要进行信源数估计且波达方向估计性能易受信源数估计误差影响的问题,提出了一种引入虚拟期望信号的未知信源数共形阵波达方向估计算法.在介绍共形阵窄带信号接收模型及自适应波束控制原理的基础上,利用最大信干噪比准则下的最优权矢量对引入虚拟期望信号后的阵列接收数据进行加权处理,以阵列输出的信噪比作为波达方向估计参数,从而实现来波信号的准确估计.整个过程不需要以信源数作为先验知识,避免了波达方向估计过程中信源数的判断环节.对所提算法进行了仿真实验,结果表明,该算法是有效可行的,且其性能要优于MUSIC算法.

关键词: 共形阵, 波达方向估计, 信源数估计, 虚拟期望信号

Abstract:

An algorithm for conformal array DOA estimation with an unknown number of sources is developed to solve the problem that most of the DOA algorithms are based on the prior knowledge of the number of sources and the estimation error of the number of sources leads to the degradation of DOA algorithm performance. This method is realized by introducing the pseudo expected signal. Firstly, the received narrow band signal of the conformal array is modeled and the adaptive beamforming theory is introduced. The optimum weight deduced by the Maximum signal to inference and noise ratio (SINR) is applied to the received signal and the pseudo expected signal and the conformal array output signal to noise ratio (SNR) is regarded as the parameter of the DOA to accomplish the estimation. During the processing, the proposed method does not need the prior knowledge of the number of sources and the signal number estimation is avoided. Finally the validity of the algorithm is verified by simulation experiments. The simulation results show that the algorithm is effective and superior to the MUSIC (multiple signal classification) algorithm.

Key words: conformal array, direction of arrival, estimation of source number, virtual pseudo expected signal