NDLI: DOA estimation of the moving targets in shallow water based on vector optimization beamforming and normal-mode theory

Content Provider	IEEE Xplore Digital Library
Author	Nan-song Li Hai-yan Song Sheng-chun Piao Qing-xin Meng
Copyright Year	2012
Description	Author affiliation: Science and Technology on Underwater Acoustic Laboratory, Harbin Engineering University, 150001, China (Nan-song Li; Sheng-chun Piao; Qing-xin Meng) \|\| School of Electrical and Information Engineering, Heilongjiang Institute of Technology, Harbin, 150050, China (Hai-yan Song)
Abstract	DOA estimation is one of the most important tasks for sonar system. However, the performance of conventional high-resolution DOA estimation methods is influenced because of the neglect of some important factors, such as effect of underwater sound channel, the array position errors and so on. In order to improve the robustness of the high-resolution DOA estimation methods, the vector optimization robust beamforming method is realized by adding a strong joint constraint to the weight vector norm and the steering vector errors. In addition, simulating the matched-field processing method, the DOA estimation of underwater moving targets can be computed by combining adaptive robust beamforming and normal-mode theory. It is shown that the adaptive beamforming which is presented in this paper has higher peak to maximum sidelobe ratio (PSR) and narrower ∼3dB beamwidth.
Starting Page	159
Ending Page	162
File Size	764276
Page Count	4
File Format	PDF
ISBN	9781467348140
DOI	10.1109/SPAWDA.2012.6464060
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Moving targets Normal mode Array signal processing Estimation Underwater acoustic signal Vectors Robustness Arrays Direction of arrival estimation Optimization Vector optimization
Content Type	Text
Resource Type	Article

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