• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学

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导向矢量失配情况下基于稀疏表示的波达方向估计算法

贾晋华,于洁潇,刘开华,赵宇   

  1. (天津大学电子信息工程学院,天津 300072)
  • 收稿日期:2016-04-25 修回日期:2016-06-16 出版日期:2017-11-25 发布日期:2017-11-25
  • 基金资助:

    国家自然科学基金(61501322,61401301)

A novel DOA estimation algorithm based on sparse
representation under steering vector mismatch

JIA Jin-hua,YU Jie-xiao,LIU Kai-hua,ZHAO Yu   

  1. (School of Electronic Information Engineering,Tianjin University,Tianjin 300072,China)
  • Received:2016-04-25 Revised:2016-06-16 Online:2017-11-25 Published:2017-11-25

摘要:

提出了一种传感器阵列导向矢量失配情况下的基于稀疏表示的信号源波达方向DOA估计算法。针对一些实际环境中噪声重尾现象严重的特点,采用合成圆对称广义高斯噪声分布对其进行模拟。考虑到实际环境中传感器自身运动以及外界环境因素的改变可能会导致传感器导向矢量产生波动,利用加权最小二乘法对波动生成的增益值进行最优估计。然后,构建信号模型的分数低阶矩FLOM矩阵,进行矢量化处理,以提高其数组维数。最后,利用稀疏表示方法重构信号模型,将信号源DOA估计转化为二阶锥规划问题进行求解,并采用奇异值分解降低运算量。仿真结果表明,本算法的信号源DOA估计具有很高的分辨率,且有效地避免了导向矢量失配对DOA估计产生的影响。
 

关键词: 噪声重尾, DOA估计, 分数低阶矩, 矢量化, 稀疏表示

Abstract:

We present a new direction-of-arrival (DOA) algorithm which is applicable to the steering vector mismatch scenario based on sparse representation. In order to deal with the heavy-tailed noise in a real environment, we adopt the complex circularly symmetric generalized Gaussian distribution to simulate noise distribution. Given that the array steering vector can be transformed by sensor self motion and environmental factors, we employ the weighting least squares approach (WLS) to estimate the optimal gain value caused by  steering vector mismatch. Then we utilize sparse representation to reconstruct the signal model and convert the DOA estimation problem to a second-order cone programming (SOCP) problem. In order to reduce computational complexity, we adopt the singular value decomposition (SVD) method. Simulation results indicate that the proposed method can not only get high-resolution DOA estimation value, but  also effectively avoid the impact of steering vector mismatch on DOA estimation.
 

Key words: heavy-tailed noise, DOA estimation, fractional lower order moment, vectorization, sparse representation