色噪声下基于差分聚焦的宽带DOA估计方法

DOA estimation of wide-band array with differential focusing under colored noise

针对色噪声下宽带阵列波达方向(DOA)估计精度差及稳健性不足的问题,本文结合协方差矩阵差分理论及特征向量空间聚焦算法提出有效解决方案.算法首先按照协方差矩阵差分理论求解差分矩阵,并对差分协方差矩阵进行特征分解,取正特征值部分对应的特征向量重构观测模型,消除色噪声及“伪峰”影响;然后,针对新观测模型,构建新的信号自相关矩阵;在此基础上,推导了不需角度预估的宽带DOA估计方法原理,即以不同频点处特征向量信号子空间为基础,求解聚焦矩阵;此外,为避免特征分解过程中零特征值所对应的特征向量对算法分辨门限的影响,依照特征值递减序列对特征向量矩阵进行重新排列,由非显著部分与信号阵列流型矩阵之间的正交性关系,重构聚焦矩阵.最后,仿真比较分析了所提算法与在噪声背景下的测向精确性、分辨能力、算法稳健性及复杂度方面的性能.理论分析及仿真结果表明,本文方法在色噪声背景下估计精度高、稳健性好,且不需要进行角度预估,复杂度低,实用性较强.

To solve the problem of wide-band direction-of-arrival(DOA)estimation in the case of colored noise,this paper proposes an effective solution combining covariance matrix difference theory and eigenvector space focusing algorithm.First,based on the covariance matrix difference theory,the difference covariance matrix was decomposed,and the observation model was reconstructed by taking the corresponding eigenvector of the positive eigenvalue part to eliminate the influence of colored noise and“pseudo”peak.Then,for the obtained observation model,a new signal autocorrelation matrix was constructed,and a wide-band DOA estimation method that requires no angle prediction was derived,which is to solve the focus matrix based on the eigenvector signal subspace at different frequency points.In addition,in order to avoid the influence of the eigenvector corresponding to zero eigenvalue on the resolution threshold,the eigenvector matrix was rearranged according to the eigenvalue decreasing sequence,and the focus matrix was reconstructed from the orthogonality relationship between the nonsalient part and the flow pattern matrix of the signal array.Finally,the performances of direction finding accuracy,resolution,robustness,and complexity of the proposed algorithm were analyzed in noise background.Theoretical analysis and simulation results indicate that the method has high accuracy and robustness in the background of colored noise with low complexity and strong practicability,and there is no need to conduct angle prediction.