Quaternion sparse decomposition algorithm for DOA estimation with acoustic vector sensor array

被引：3
|
作者：
Zhao Y. [1 ]
Li X.-B. [1 ]
Shi Y.-W. [1 ]
机构：
[1] School of Communication Engineering, Jilin University, Changchun
来源：
Zhao, Yang (zhaoyang_yes@163.com) | 2018年 / Chinese Academy of Sciences卷 / 26期
关键词：
Acoustic vector array; Parameters estimation; Quaternion; Sparse decomposition;
D O I：
10.3788/OPE.20182603.0715
中图分类号：
学科分类号：
摘要：
This work extended sparse decomposition (SD) into quaternion space in order to find a better sparse representation for acoustic vector array (AVA). A novel sparse decomposition algorithm based on the well-known orthogonal matching pursuit (OMP) for quaternionic signals was proposed and it was used to solve the question of direction of arrival (DOA) estimation of AVA in small snapshot number, coherent signal source and low signal noise ratio (SNR) case. Compare with the complex field SD algorithm, The results illustrate that the atomic length of the over-complete dictionary is reduced to one-third of that from the long vector model, while errors in DOA estimation are effectively eliminated using the long vector method when the true angles of DOA estimation lie within 1°. Simulation results verify the validity of this algorithm. © 2018, Science Press. All right reserved.
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页码：715 / 722
页数：7
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