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Smart Magnetic Sensors and Applications
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Smart Magnetic Sensors and Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 25 May 2026 | Viewed by 996

Special Issue Editors

Dr. Yuanping Xu

E-Mail Website
Guest Editor
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Interests: magnetic levitation; smart sensors and actuators; vibration control; rotor dynamics
Special Issues, Collections and Topics in MDPI journals
Dr. Lu Yang

E-Mail Website
Guest Editor
College of Civil and Transportation Engineering, HoHai University, Nanjing 210016, China
Interests: smart materials and structures; force sensors; vibration control
Dr. Qiuying Zhao

E-Mail Website
Guest Editor
School of Mechanical Engineering, Suzhou University of Science and Technology, Suzhou 215009, China
Interests: smart materials and structures; force sensors; flexible sensors

Special Issue Information

Dear Colleagues,

Magnetic sensors have become indispensable across a wide range of industries, from the healthcare and automotive industries to robotics and consumer electronics. As technological advancements continue to accelerate, these sensors are set to play an even more central role in shaping the future of various sectors. Their unique ability to function effectively in diverse and challenging environments, along with their precision and adaptability, ensures they will remain at the forefront of developing smarter, more connected systems that enhance safety, efficiency, and sustainability in daily life.

This Special Issue aims to showcase cutting-edge research and innovations focused on overcoming the challenges of improving the performance and miniaturization of smart magnetic sensors. It also explores the growing potential of these sensors in key applications such as environmental monitoring, wearable technology, and industrial automation. Topics of interest include, but are not limited to, the following:

  • Novel magnetic materials and structures;
  • Smart sensor networks;
  • Intelligent signal processing;
  • Miniaturization and integration;
  • Sensor fusion and multi-sensor integration;
  • Advanced sensor calibration and standardization;
  • Extended applications in harsh environments, aerospace, and IoT;
  • Wearable and healthcare applications;
  • Autonomous systems and robotics.

Dr. Yuanping Xu
Dr. Lu Yang
Dr. Qiuying Zhao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • novel magnetic materials and structures
  • smart sensor networks
  • intelligent signal processing
  • miniaturization and integration
  • sensor fusion and multi-sensor integration
  • advanced sensor calibration and standardization
  • extended applications in harsh environments, aerospace, and IoT
  • wearable and healthcare applications
  • autonomous systems and robotics

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Published Papers (1 paper)

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Research

16 pages, 2639 KB  
Article
Magnetic Heterodyne Target Proximal Distance Estimate Using Extended N-th-Pole Magnetic Dipole Model via Iterative Extended Kalman Filter
by Xuyi Miao, Yipeng Li, Zumeng Jiang, Shaojie Ma, He Zhang, Peng Liu and Keren Dai
Sensors 2026, 26(9), 2792; https://doi.org/10.3390/s26092792 - 30 Apr 2026
Viewed by 375
Abstract
Anti-collision detection technologies primarily rely on optical, radar, or laser sensors; however, their performance often deteriorates severely under adverse weather conditions (e.g., rain, snow, fog) or in scenarios involving visual occlusion. By contrast, magnetic anomaly detection leverages perturbations in the geomagnetic field induced [...] Read more.
Anti-collision detection technologies primarily rely on optical, radar, or laser sensors; however, their performance often deteriorates severely under adverse weather conditions (e.g., rain, snow, fog) or in scenarios involving visual occlusion. By contrast, magnetic anomaly detection leverages perturbations in the geomagnetic field induced by target objects (e.g., vehicles, metallic obstacles), exhibiting intrinsic all-weather operability and strong anti-interference capability. Nevertheless, conventional magnetic anomaly detection methods suffer from the limited applicability of the magnetic dipole model, which only affords coarse positioning accuracy and is predominantly suited for long-range targets. To address this limitation, this paper proposes an Extended N-th-Pole Magnetic Dipole (E-NMD) model that improves accuracy by analyzing the Lagrangian cosine term and rigorously constraining truncation errors under specific operational conditions. Experimental results demonstrate that, for steel with a relative permeability of 200, the model achieves a fitting variance of 99.87%. Furthermore, to overcome the inversion difficulties arising when the strength of short-range magnetic anomalies is comparable to sensor noise, an Adaptive Iterative Extended Kalman Filter (AI-EKF) is developed to enable robust noise suppression and precise distance estimation. Results indicate that E-NMD outperforms the traditional N-th-Pole Magnetic Dipole (NMD) model in proximal state estimation, achieving a 39.62% reduction in Root Mean Square Error (RMSE). Finally, in light of parameter uncertainty in magnetic anomaly targets under real-world conditions, a Dual-Mode Pairwise Iterative Extended Kalman Filter (DI-EKF) is introduced to jointly estimate parameters and system states, yielding an 89% reduction in RMSE compared to AI-EKF. Full article
(This article belongs to the Special Issue Smart Magnetic Sensors and Applications)
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