Micro Sensors and Devices for Ocean Engineering

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "A:Physics".

Deadline for manuscript submissions: 31 July 2026 | Viewed by 735

Special Issue Editor


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Guest Editor
School of Aerospace Engineering, Xiamen University, Xiamen 361005, China
Interests: MEMS; sensors; ocean instrument

Special Issue Information

Dear Colleagues,

The extreme complexity of the marine environment imposes stringent demands on the reliability, stability, and accuracy of sensing technologies—with core challenges rooted in advanced manufacturing processes. This Special Issue focuses on cutting-edge sensor technologies for ocean observation and detection, showcasing integrated innovations spanning from microscale devices to macroscale system-level integration. Emphasis is placed on novel sensors for key ocean parameters, supported by manufacturing advances in micro/nanofabrication, biomimetic structuring, multifunctional integration, and corrosion- and high-pressure-resistant encapsulation. We welcome contributions on manufacturing methods, innovative materials, process optimization, and in situ performance validation of marine sensors. Relevant application domains include, but are not limited to, sensing of temperature, salinity, pressure, acoustic signals, flow velocity, electric and magnetic fields, pH, dissolved oxygen, and hydrogen. This Special Issue aims to drive technological breakthroughs in marine sensor manufacturing and help build the device-level foundation for next-generation intelligent, long-endurance, and high-resolution ocean observation networks.

Prof. Dr. Chenyang Xue
Guest Editor

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Keywords

  • advanced ocean sensing
  • marine microsensors
  • micro-nano fabrication

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Published Papers (1 paper)

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Research

17 pages, 3304 KB  
Article
High-Resolution Azimuth Estimation Method Based on a Pressure-Gradient MEMS Vector Hydrophone
by Xiao Chen, Ying Zhang and Yujie Chen
Micromachines 2026, 17(2), 167; https://doi.org/10.3390/mi17020167 - 27 Jan 2026
Cited by 2 | Viewed by 518
Abstract
The pressure-gradient Micro-Electro-Mechanical Systems (MEMS) vector hydrophone is a novel type of sensor capable of simultaneously acquiring both scalar and vectorial information within an acoustic field. Conventional azimuth estimation methods struggle to achieve high-resolution localization using a single pressure-gradient MEMS vector hydrophone. In [...] Read more.
The pressure-gradient Micro-Electro-Mechanical Systems (MEMS) vector hydrophone is a novel type of sensor capable of simultaneously acquiring both scalar and vectorial information within an acoustic field. Conventional azimuth estimation methods struggle to achieve high-resolution localization using a single pressure-gradient MEMS vector hydrophone. In practical marine environments, the multiple signal classification (MUSIC) algorithm is hampered by significant resolution performance loss. Similarly, the complex acoustic intensity (CAI) method is constrained by a high-resolution threshold for multiple targets, often resulting in inaccurate azimuth estimates. Therefore, a cross-spectral model between the acoustic pressure and the particle velocity for the pressure-gradient MEMS vector hydrophone was established. Integrated with an improved particle swarm optimization (IPSO) algorithm, a high-resolution azimuth estimation method utilizing this hydrophone is proposed. Furthermore, the corresponding Cramér-Rao Bound is derived. Simulation results demonstrate that the proposed algorithm accurately resolves two targets separated by only 5° at a low signal-to-noise ratio (SNR) of 5 dB, boasting a root mean square error of approximately 0.35° and a 100% success rate. Compared with the CAI method and the MUSIC algorithm, the proposed method achieves a lower resolution threshold and higher estimation accuracy, alongside low computational complexity that enables efficient real-time processing. Field tests in an actual seawater environment validate the algorithm’s high-resolution performance as predicted by simulations, thus confirming its practical efficacy. The proposed algorithm addresses key limitations in underwater detection by enhancing system robustness and offering high-resolution azimuth estimation. This capability holds promise for extending to multi-target scenarios in complex marine settings. Full article
(This article belongs to the Special Issue Micro Sensors and Devices for Ocean Engineering)
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