Shi Juan, Zhang Qunfei, Tan Weijie, Mao Linlin, Huang Lihuan, Shi Wentao
School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.
State Key Laboratory of Public Big Data, Guizhou University, Guiyang 550025, China.
Entropy (Basel). 2020 Mar 20;22(3):359. doi: 10.3390/e22030359.
In underwater acoustic signal processing, direction of arrival (DOA) estimation can provide important information for target tracking and localization. To address underdetermined wideband signal processing in underwater passive detection system, this paper proposes a novel underdetermined wideband DOA estimation method equipped with the nested array (NA) using focused atomic norm minimization (ANM), where the signal source number detection is accomplished by information theory criteria. In the proposed DOA estimation method, especially, after vectoring the covariance matrix of each frequency bin, each corresponding obtained vector is focused into the predefined frequency bin by focused matrix. Then, the collected averaged vector is considered as virtual array model, whose steering vector exhibits the Vandermonde structure in terms of the obtained virtual array geometries. Further, the new covariance matrix is recovered based on ANM by semi-definite programming (SDP), which utilizes the information of the Toeplitz structure. Finally, the Root-MUSIC algorithm is applied to estimate the DOAs. Simulation results show that the proposed method outperforms other underdetermined DOA estimation methods based on information theory in term of higher estimation accuracy.
在水下声学信号处理中,波达方向(DOA)估计可为目标跟踪和定位提供重要信息。为解决水下无源探测系统中欠定宽带信号处理问题,本文提出一种基于聚焦原子范数最小化(ANM)的新型欠定宽带DOA估计方法,该方法采用嵌套阵列(NA),其中信号源数量检测通过信息论准则完成。在所提出的DOA估计方法中,特别地,在对每个频率 bin 的协方差矩阵进行矢量化后,通过聚焦矩阵将每个相应得到的矢量聚焦到预定义的频率 bin 中。然后,将收集到的平均矢量视为虚拟阵列模型,其导向矢量根据所获得的虚拟阵列几何形状呈现范德蒙德结构。进一步地,通过半定规划(SDP)基于ANM恢复新的协方差矩阵,该半定规划利用了托普利兹结构的信息。最后,应用根 MUSIC 算法估计波达方向。仿真结果表明,所提出的方法在估计精度方面优于其他基于信息论的欠定DOA估计方法。