Research on an Improved Compressive Matched Field Localization Algorithm for Arctic Double Channels

LÜ Yujiao; LIU Chonglei; ZHANG Yangfan; HUANG Haining

doi:10.11999/JEIT211445

Volume 44 Issue 6

Jun. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(6): 1991-1998

LÜ Yujiao, LIU Chonglei, ZHANG Yangfan, HUANG Haining. Research on an Improved Compressive Matched Field Localization Algorithm for Arctic Double Channels[J]. Journal of Electronics & Information Technology, 2022, 44(6): 1991-1998. doi: 10.11999/JEIT211445

Citation:

LÜ Yujiao, LIU Chonglei, ZHANG Yangfan, HUANG Haining. Research on an Improved Compressive Matched Field Localization Algorithm for Arctic Double Channels[J]. Journal of Electronics & Information Technology, 2022, 44(6): 1991-1998. doi: 10.11999/JEIT211445

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Research on an Improved Compressive Matched Field Localization Algorithm for Arctic Double Channels

doi: 10.11999/JEIT211445

LÜ Yujiao^{1, 2, 3},
LIU Chonglei^{1, 2},
ZHANG Yangfan^{1, 2},
HUANG Haining^{1, 2
,
,}

1.
Institute of Acoustic, Chinese Academic of Sciences, Beijing 100190, China
2.
Key Laboratory of Science and Technology on Advanced Underwater Acoustic Signal Processing, Chinese Academy of Sciences, Beijing 100190, China
3.
University of Chinese Academic of Sciences, Beijing 100190, China

Funds: The National Key Research and Development Program of China (2021YFC2801200)

Received Date: 2021-12-06
Rev Recd Date: 2022-03-28

Available Online: 2022-04-07

Publish Date: 2022-06-21

Abstract

Abstract

Arctic underwater channels are complex. Matched field processing is a kind of target localizing method that can combine environmental information with signal processing methods. The target position can be accurately estimated when model is matched. However, due to the complex environment and the lack of key information, it is difficult to match the model completely, which leads to the problem of inaccurate estimation. In this paper, an improved matched field algorithm is proposed. Based on the principle of phase normalization, the sparse model is optimized, and the normalized information of arrays is used for matching to eliminate the influence of signal spectrum. The simulation result shows that the accuracy of the improved method is higher than that of the former method. The experimental data processing shows that the improved method has less error in target position estimation and higher resolution than the conventional matched field processing method.
- Matched field localization,
- Array processing,
- Compressive sensing,
- Arctic

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References(20)

References

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