Robust Adaptive Matched Field Processing of Rank Reduction for Source Localization under Internal Solitary Waves

LI Jiemeihui; SHI Yang; YANG Yixin; HUANG Xiaodong

doi:10.11999/JEIT211333

Volume 44 Issue 6

Jun. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(6): 1897-1905

LI Jiemeihui, SHI Yang, YANG Yixin, HUANG Xiaodong. Robust Adaptive Matched Field Processing of Rank Reduction for Source Localization under Internal Solitary Waves[J]. Journal of Electronics & Information Technology, 2022, 44(6): 1897-1905. doi: 10.11999/JEIT211333

Citation:

LI Jiemeihui, SHI Yang, YANG Yixin, HUANG Xiaodong. Robust Adaptive Matched Field Processing of Rank Reduction for Source Localization under Internal Solitary Waves[J]. Journal of Electronics & Information Technology, 2022, 44(6): 1897-1905. doi: 10.11999/JEIT211333

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Robust Adaptive Matched Field Processing of Rank Reduction for Source Localization under Internal Solitary Waves

doi: 10.11999/JEIT211333

LI Jiemeihui^{1, 2},
SHI Yang^{1, 2
,
,},
YANG Yixin^{1, 2},
HUANG Xiaodong³

1.
School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710000, China
2.
Shaanxi Key Laboratory of Underwater Information Technology, Xi’an 710000, China
3.
Physical Oceanography Laboratory, Ocean University of China, Qingdao 266000, China

Funds: The National Natural Science Foundation of China (41906160, 11974286, 12174312)

Received Date: 2021-11-25
Rev Recd Date: 2022-05-19

Available Online: 2022-05-24

Publish Date: 2022-06-21

Abstract

Abstract

The mismatch of sound speed induced by internal solitary waves will cause the inaccurate estimation in the matched field processing for source localization. In this paper, a robust Adaptive Matched Field Processing method of Rank Reduction (RR-AMFP) for internal solitary waves is proposed. Based on the traditional adaptive matched field processing algorithm, this method integrates dominant mode rejection beamforming, and reduces the rank of sampling covariance matrix by eigen-decomposition, and suppresses the noise space. Meanwhile, a suppressing coefficient and a weighting factor are used to calculate the weight vector in the matching process, and the mismatched coping vectors are detected. Therefore, this method can maintain better robustness in the internal solitary wave environment, and the reduction of rank also shortens the calculation time. The simulation results show that this method can accurately estimate the source location under a single internal solitary wave, but the internal solitary wave train with large amplitude will still lead to more errors of estimation. The estimated distance error is 3.3% and depth error is 1.5% in the localization experiment of internal solitary waves in the South China Sea, which belongs to reliable localization. The experiment results demonstrate the effectiveness of the method in the actual environment with internal solitary waves.
- Underwater source localization,
- Adaptive matched field processing,
- Internal solitary wave,
- Rank reduction,
- South China Sea

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References(18)

References

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