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Research on underwater target signal orientation estimation based on smoothness priors approach

Wenqing Zhang (State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan, China)
Guojun Zhang (State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan, China)
Zican Chang (State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan, China)
Yabo Zhang (State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan, China)
YuDing Wu (State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan, China)
YuHui Zhang (State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan, China)
JiangJiang Wang (State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan, China)
YuHao Huang (State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan, China)
RuiMing Zhang (State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan, China)
Wendong Zhang (State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan, China)

Sensor Review

ISSN: 0260-2288

Article publication date: 23 October 2024

Issue publication date: 20 November 2024

26

Abstract

Purpose

This paper aims to address the challenges in hydroacoustic signal detection, signal distortion and target localization caused by baseline drift. The authors propose a combined algorithm that integrates short-time Fourier transform (STFT) detection, smoothness priors approach (SPA), attitude calibration and direction of arrival (DOA) estimation for micro-electro-mechanical system vector hydrophones.

Design/methodology/approach

Initially, STFT method screens target signals with baseline drift in low signal-to-noise ratio environments, facilitating easier subsequent processing. Next, SPA is applied to the screened target signal, effectively removing the baseline drift, and combined with filtering to improve the signal-to-noise ratio. Then, vector channel amplitudes are corrected using attitude correction with 2D compass data. Finally, the absolute target azimuth is estimated using the minimum variance distortion-free response beamformer.

Findings

Simulation and experimental results demonstrate that the SPA outperforms high-pass filtering in removing baseline drift and is comparable to the effectiveness of variational mode decomposition, with significantly shorter processing times, making it more suitable for real-time applications. The detection performance of the STFT method is superior to instantaneous correlation detection and sample entropy methods. The final DOA estimation achieves an accuracy within 2°, enabling precise target azimuth estimation.

Originality/value

To the best of the authors’ knowledge, this study is the first to apply SPA to baseline drift removal in hydroacoustic signals, significantly enhancing the efficiency and accuracy of signal processing. It demonstrates the method’s outstanding performance in the field of underwater signal processing. In addition, it confirms the reliability and feasibility of STFT for signal detection in the presence of baseline drift.

Keywords

Acknowledgements

This work was supported by National Key Research and Development Project (Grant No.2019YFC0119800), National Natural Science Foundation of China as National Major Scientiffc Instruments Development Project (Grant No. 61927807), National Natural Science Foundation of China (Grant No. 52175553), Shanxi Province Basic Research Project (Grant No. 202103021224203), and The Fund for Shanxi ‘1331 Project’ Key Subject Construction and Innovation Special Zone Project.

Citation

Zhang, W., Zhang, G., Chang, Z., Zhang, Y., Wu, Y., Zhang, Y., Wang, J., Huang, Y., Zhang, R. and Zhang, W. (2024), "Research on underwater target signal orientation estimation based on smoothness priors approach", Sensor Review, Vol. 44 No. 6, pp. 762-782. https://doi.org/10.1108/SR-06-2024-0558

Publisher

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Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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