摘要
Efficiently performing high-resolution direction of arrival(DOA)estimation under low signal-to-noise ratio(SNR)conditions has always been a challenge task in the literatures.Obvi-ously,in order to address this problem,the key is how to mine or reveal as much DOA related in-formation as possible from the degraded array outputs.However,it is certain that there is no per-fect solution for low SNR DOA estimation designed in the way of winner-takes-all.Therefore,this paper proposes to explore in depth the complementary DOA related information that exists in spa-tial spectrums acquired by different basic DOA estimators.Specifically,these basic spatial spec-trums are employed as the input of multi-source information fusion model.And the multi-source in-formation fusion model is composed of three heterogeneous meta learning machines,namely neural networks(NN),support vector machine(SVM),and random forests(RF).The final meta-spec-trum can be obtained by performing a final decision-making method.Experimental results illus-trate that the proposed information fusion based DOA estimation method can really make full use of the complementary information in the spatial spectrums obtained by different basic DOA estim-ators.Even under low SNR conditions,promising DOA estimation performance can be achieved.
基金
the National Natural Science Foundation of China(Nos.11774073 and 51279033).
作者简介
Yun Wu was born in Daqing,China in 1980.She received the B.S.and M.S.degrees in electronic engineering from the Northeast Petroleum University,Daqing,in 2002 and 2008 respectively.She is currently working toward the Ph.D.degree of information and communication engineering in the College of Underwater Acoustic Engineering,Harbin Engineering University.She is also an associate professor at the Northeast Petroleum University,Daqing,China.Her research interests are underwater sig-nal processing,array processing,and big data based pattern recognition;Corresponding author:Xiukun Li received the B.S.in electronic engineering from Harbin Ship Engineering Institute,in 1984,the M.S.and Ph.D.degrees in underwater acoustic engineering from Harbin Engineering University(HEU)in 1989 and in 2000,respectively.Since 2001,she has been a professor and doctoral supervisor at HEU.Her research interests include underwater signal processing,array processing,and target detection,and etc.She has published more than 60 peer-reviewed papers,and she is also the inventor or coinventor of more than 10 patents.Email:lixiukun@hrbeu.edu.cn;Zhimin Cao received the B.S.degree in electronic engineering from Daqing Petroleum Institute,Daqing,China,in 2003,the M.S.and Ph.D.degrees in informa-tion and communication engineering from Harbin Institute of Technology,Harbin,China,in 2008 and in 2016 respectively.In 2020,he has finished his postdoctoral work in Daqing OilFiled Postdoctoral Workstation.He is now an associate professor in the School of Physical and Electronic Engineering,Northeast Petroleum University.His research interests are signal processing and pattern recognition,geological Big Data analysis and application.He has published more than 40 peer-review papers.
