Matched steering vector searching based direction-of-arrival estimation using acoustic vector sensor array

The acoustic vector sensor (AVS) array is a powerful tool for underwater target’s direction-of-arrival (DOA) estimation without any bearing ambiguities. However, traditional DOA estimation algorithms generally suffer from low signal-to-noise ratio (SNR) as well as snapshot deficiency. By exploiting...

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Veröffentlicht in:EURASIP journal on wireless communications and networking Jg. 2019; H. 1; S. 1 - 10
Hauptverfasser: Ao, Yu, Wang, Ling, Wan, Jianwei, Xu, Ke
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 29.08.2019
Springer Nature B.V
SpringerOpen
Schlagworte:
Acoustic noise
Acoustic vector sensor (AVS) array
Algorithms
Amplitudes
Communications Engineering
Computer simulation
Direction of arrival
Direction-of-arrival (DOA) estimation
Distributed Big Data Processing in SCADA Communication Networks
Engineering
Information Systems Applications (incl.Internet)
Minimum variance distortionless response (MVDR)
Networks
Pseudo-spatial spectrum
Searching
Sensor arrays
Signal to noise ratio
Signal,Image and Speech Processing
Steering
Steering vector
Underwater acoustics
Pseudo-spatial spectrum
Steering vector
Acoustic vector sensor (AVS) array
Direction-of-arrival (DOA) estimation
Minimum variance distortionless response (MVDR)
ISSN:1687-1499, 1687-1472, 1687-1499
Online-Zugang:Volltext
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Zusammenfassung:The acoustic vector sensor (AVS) array is a powerful tool for underwater target’s direction-of-arrival (DOA) estimation without any bearing ambiguities. However, traditional DOA estimation algorithms generally suffer from low signal-to-noise ratio (SNR) as well as snapshot deficiency. By exploiting the properties of the minimum variance distortionless response (MVDR) beamformer, a new DOA estimation method basing on matched steering vector searching is proposed in this article. Firstly, attain the rough estimate of the desired DOA using the traditional algorithms. Secondly, set a small angular interval around the crudely estimated DOA. Thirdly, make the view direction vary in the view interval, and for each view direction, calculate the beam amplitude response of the MVDR beamformer, and find the minimum of the amplitude response. Finally, the pseudo-spatial spectrum is achieved, and the accurate estimate of the desired DOA can be obtained through peak searching. Computer simulations verify that the proposed method is efficient in DOA estimation, especially in low SNR and insufficient snapshot data scenarios.
Bibliographie:ObjectType-Article-1
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ISSN:1687-1499
1687-1472
1687-1499
DOI:10.1186/s13638-019-1536-8