文章基本信息

标题：UNDERWATER TARGET DIRECTION OF ARRIVAL ESTIMATION BY SMALL ACOUSTIC SENSOR ARRAY BASED ON SPARSE BAYESIAN LEARNING
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作者：Wang Biao ; He Cheng
期刊名称：Polish Maritime Research
电子版ISSN：2083-7429
出版年度：2017
卷号：24
期号：2
页码：95-102
DOI：10.1515/pomr-2017-0070
语种：English
出版社：Sciendo
摘要：Assuming independently but identically distributed sources,the traditional DOA (direction of arrival) estimation method of underwater acoustic target normally has poor estimation performance and provides inaccurate estimation results.To solve this problem,a new high-accuracy DOA algorithm based on sparse Bayesian learning algorithm is proposed in terms of temporally correlated source vectors.In novel method,we regarded underwater acoustic source as a first-order auto-regressive process.And then we used the new algorithm of multi-vector SBL to reconstruct the signal spatial spectrum.Then we used the CS-MMV model to estimate the DOA.The experiment results have shown the novel algorithm has a higher spatial resolution and estimation accuracy than other DOA algorithms in the cases of less array element space and less snapshots.
关键词：DOA;underwater acoustic signal processing;sparse Bayesian learning;temporally correlated source