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Research on DOA Estimation Based on Acoustic Energy Flux Detection Using a Single MEMS Vector Hydrophone.
Zhang, Xiaoyong; Zhang, Guojun; Shang, Zhenzhen; Zhu, Shan; Chen, Peng; Wang, Renxin; Zhang, Wendong.
Afiliação
  • Zhang X; State Key Laboratory of Dynamic Testing Technology, North University of China, Taiyuan 030051, China.
  • Zhang G; Department of Intelligence and Automation, Taiyuan University, Taiyuan 030032, China.
  • Shang Z; State Key Laboratory of Dynamic Testing Technology, North University of China, Taiyuan 030051, China.
  • Zhu S; State Key Laboratory of Dynamic Testing Technology, North University of China, Taiyuan 030051, China.
  • Chen P; State Key Laboratory of Dynamic Testing Technology, North University of China, Taiyuan 030051, China.
  • Wang R; State Key Laboratory of Dynamic Testing Technology, North University of China, Taiyuan 030051, China.
  • Zhang W; State Key Laboratory of Dynamic Testing Technology, North University of China, Taiyuan 030051, China.
Micromachines (Basel) ; 12(2)2021 Feb 08.
Article em En | MEDLINE | ID: mdl-33567607
ABSTRACT
The principle of acoustic energy flux detection method using a single micro electromechanical system (MEMS) vector hydrophone is analyzed in this paper. The probability distribution of acoustic energy flux and the weighted histogram algorithm are discussed. Then, an improved algorithm is proposed. Based on the algorithm, the distribution range of the energy is obtained by a sliding window, the energy center of gravity in the range is considered as the result of direction of arrival (DOA) estimation, and it is proved to be the maximum likelihood estimation of the target direction. The simulation results show that, with the signal to noise ratio (SNR) from -10 dB to 10 dB, the root mean square error (RMSE) of the improved algorithm is reduced by 47.8% on average, and is more accurate in the presence of interference. The experimental results of lake test are consistent with the theory analysis and simulation results.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article