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Sensors 2017, 17(6), 1345; doi:10.3390/s17061345

A Noise Removal Method for Uniform Circular Arrays in Complex Underwater Noise Environments with Low SNR

1
School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China
2
Key Laboratory of Ocean Acoustics and Sensing, Ministry of Industry and Information Technology, Xi’an 710072, China
3
School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710072, China
*
Author to whom correspondence should be addressed.
Received: 19 April 2017 / Revised: 6 June 2017 / Accepted: 6 June 2017 / Published: 9 June 2017
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Abstract

Generally, many beamforming methods are derived under the assumption of white noise. In practice, the actual underwater ambient noise is complex. As a result, the noise removal capacity of the beamforming method may be deteriorated considerably. Furthermore, in underwater environment with extremely low signal-to-noise ratio (SNR), the performances of the beamforming method may be deteriorated. To tackle these problems, a noise removal method for uniform circular array (UCA) is proposed to remove the received noise and improve the SNR in complex noise environments with low SNR. First, the symmetrical noise sources are defined and the spatial correlation of the symmetrical noise sources is calculated. Then, based on the preceding results, the noise covariance matrix is decomposed into symmetrical and asymmetrical components. Analysis indicates that the symmetrical component only affect the real part of the noise covariance matrix. Consequently, the delay-and-sum (DAS) beamforming is performed by using the imaginary part of the covariance matrix to remove the symmetrical component. However, the noise removal method causes two problems. First, the proposed method produces a false target. Second, the proposed method would seriously suppress the signal when it is located in some directions. To solve the first problem, two methods to reconstruct the signal covariance matrix are presented: based on the estimation of signal variance and based on the constrained optimization algorithm. To solve the second problem, we can design the array configuration and select the suitable working frequency. Theoretical analysis and experimental results are included to demonstrate that the proposed methods are particularly effective in complex noise environments with low SNR. The proposed method can be extended to any array. View Full-Text
Keywords: underwater ambient noise; sensor array signal processing; signal-to-noise ratio; beamforming; noise removal underwater ambient noise; sensor array signal processing; signal-to-noise ratio; beamforming; noise removal
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Xia, H.; Yang, K.; Ma, Y.; Wang, Y.; Liu, Y. A Noise Removal Method for Uniform Circular Arrays in Complex Underwater Noise Environments with Low SNR. Sensors 2017, 17, 1345.

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