2D DOA Estimation of Coherent Signals with a Separated Linear Acoustic Vector-Sensor Array  

作　　者：Sheng Liu Jing Zhao Decheng Wu Yiwang Huang Kaiwu Luo 

机构地区：[1]School of Data Science,Tongren University,Tongren 554300,China [2]School of Automation,Chongqing University of Posts and Telecommunications,Chongqing 400065,China

出　　处：《China Communications》2024年第2期155-165,共11页中国通信（英文版）

基　　金：supported by the National Natural Science Foundation of China (62261047,62066040);the Foundation of Top-notch Talents by Education Department of Guizhou Province of China (KY[2018]075);the Science and Technology Foundation of Guizhou Province of China (ZK[2022]557,[2020]1Y004);the Science and Technology Research Program of the Chongqing Municipal Education Commission (KJQN202200637);PhD Research Start-up Foundation of Tongren University (trxyDH1710);Tongren Science and Technology Planning Project ((2018)22)。

摘　　要：In this paper, a two-dimensional(2D) DOA estimation algorithm of coherent signals with a separated linear acoustic vector-sensor(AVS) array consisting of two sparse AVS arrays is proposed. Firstly,the partitioned spatial smoothing(PSS) technique is used to construct a block covariance matrix, so as to decorrelate the coherency of signals. Then a signal subspace can be obtained by singular value decomposition(SVD) of the covariance matrix. Using the signal subspace, two extended signal subspaces are constructed to compensate aperture loss caused by PSS.The elevation angles can be estimated by estimation of signal parameter via rotational invariance techniques(ESPRIT) algorithm. At last, the estimated elevation angles can be used to estimate automatically paired azimuth angles. Compared with some other ESPRIT algorithms, the proposed algorithm shows higher estimation accuracy, which can be proved through the simulation results.

关 键 词：acoustic vector-sensor coherent signals extended signal subspace sparse array 

分 类 号：TN911.7[电子电信—通信与信息系统] TP212[电子电信—信息与通信工程]