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Microwave and Millimeter-Wave Sensing and Imaging on Wearable, Vehicular, and Portable Platforms

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

Deadline for manuscript submissions: 25 November 2026 | Viewed by 3382

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Special Issue Editor

Prof. Dr. Natalia K. Nikolova

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Guest Editor

Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada
Interests: microwave and millimeter-wave imaging and detection; synthetic aperture radar; inverse scattering; image-reconstruction algorithms; ultra-wideband radar; antennas; high-frequency computer-aided analysis and design
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Special Issue Information

Dear Colleagues,

The start of the 21st century marked a remarkable advancement in high-frequency microelectronics and the advent of the microwave and millimeter-wave radar systems on chips. This has spurred exponential growth in the research and development of new applications in sensing and imaging, including vehicular guidance, non-destructive testing, biomedical diagnostics, monitoring, security, surveillance, non-destructive testing, and inspection.

This Special Issue aims to highlight original research and informative reviews of the latest advances in the fields of radio-frequency (RF), microwave, and millimeter-wave sensing and imaging with a focus on emerging devices and systems amenable to portable, vehicular, and wearable deployment.

Topics of interest include but are not limited to the following:

Microwave and millimeter-wave sensors and systems;
Microwave and millimeter-wave imaging systems and antennas;
Microwave signal processing for target and fault detection, classification, and identification, as well as target tracking;
Advancing microwave and millimeter-wave image-reconstruction algorithms toward real-time processing, the processing of sparse and randomly sampled data, data fusion, etc.;
Challenges and solutions for high-frequency sensing and imaging on mobile and wearable platforms;
Microwave sensing and imaging in biology and medicine, environmental monitoring, non-destructive testing, and new emerging applications;
Radiometry in microwave sensing and imaging.

Prof. Dr. Natalia K. Nikolova
Guest Editor

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Keywords

RF and microwave sensors
millimeter-wave sensors
microwave sensing networks
microwave imaging
millimeter-wave imaging
radar imaging
synthetic aperture radar
airborne radar
vehicular radars
wearable and portable sensing and imaging systems
biomedical RF/microwave sensing and imaging

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Published Papers (5 papers)

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Research

26 pages, 3122 KB

Open AccessArticle

A 94 GHz Millimeter-Wave Radar System for Remote Vehicle Height Measurement to Prevent Bridge Collisions

by Natan Steinmetz, Eyal Magori, Yael Balal, Yonatan B. Sudai and Nezah Balal

Sensors 2026, 26(6), 1921; https://doi.org/10.3390/s26061921 - 18 Mar 2026

Viewed by 423

Abstract

Collisions between over-height vehicles and low-clearance bridges cause infrastructure damage and pose safety risks. Existing detection systems rely primarily on optical sensors, which suffer from performance degradation in adverse weather conditions. This paper presents an alternative approach based on a 94 GHz millimeter-wave radar that achieves velocity-independent height measurement. The proposed technique exploits the ratio of Doppler shifts from two scattering centers on a vehicle, specifically the roof and the wheel–road interface. This ratio depends only on the measurement geometry, as the unknown vehicle velocity cancels algebraically, enabling direct height computation without speed measurement. The paper provides a closed-form height estimation model, analyzes the trade-off between frequency resolution and geometric constancy during integration, and presents experimental validation using a scaled laboratory testbed. An optical tracking system is used solely for ground-truth validation in the laboratory and is not required for operational deployment. Results across six test cases with heights ranging from 20 cm to 46 cm demonstrate an average absolute error of 0.60 cm and relative errors below 3.3 percent. A scaling analysis for representative full-scale geometries indicates that at highway speeds of 80 km/h, integration times in the millisecond range (approximately 3–18 ms for representative 20–50 m measurement standoff) are feasible; warning distance can be extended independently by upstream radar placement. The expected advantage in fog, rain, and dust is based on established W-band propagation characteristics; dedicated adverse-weather and full field validation (including multipath, clutter, and multi-vehicle scenarios) remain future work. Full article

(This article belongs to the Special Issue Microwave and Millimeter-Wave Sensing and Imaging on Wearable, Vehicular, and Portable Platforms)

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24 pages, 14844 KB

Open AccessArticle

A Resonator-Based Flexible Antenna for Non-Invasive Deep Brain Temperature Sensing with Microwave Radiometry

by Golap Kanti Dey, Mohammad Vaseem, Natalia K. Nikolova, Atif Shamim and Chih-Hung Chen

Sensors 2026, 26(5), 1699; https://doi.org/10.3390/s26051699 - 8 Mar 2026

Viewed by 540

Abstract

We present a circular complementary split ring resonator (CCSRR) flexible antenna operating in the 1.4 GHz radio-astronomy quiet frequency band. The antenna is designed for microwave non-invasive brain temperature sensing of an infant’s head to aid in the therapeutic hypothermia treatment of hypoxic–ischemic encephalopathy (HIE) and traumatic brain injury (TBI). The proposed metamaterial-inspired antenna is designed on a flexible Kapton substrate with a biocompatible Polydimethylsiloxane (PDMS) protective superstrate layer. For brain temperature measurement, the flexible antenna is placed directly on the scalp to collect thermal noise power from the underlying tissue layers. The received thermal power is to be delivered to a sensitive microwave radiometer. The CCSRR antenna exhibits sharp frequency selectivity at 1.4 GHz with inherent filtering capability, strong field confinement, and excellent suppression of out-of-tissue (external) electromagnetic interference and thermal noise contributions. To closely match the realistic scenario, the CCSRR antenna, initially designed in a planar multi-layer configuration, is investigated in various bending configurations (cylindrical and spherical) with a curvature radius of 55 mm. The results indicate stable performance under bending. Good agreement between simulated and on-body measured results is observed in the desired frequency band. Full article

(This article belongs to the Special Issue Microwave and Millimeter-Wave Sensing and Imaging on Wearable, Vehicular, and Portable Platforms)

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30 pages, 58698 KB

Open AccessArticle

MMPFNet: A Novel Lightweight Road Target Detection Method of FMCW Radar Based on Hypergraph Mechanism and Attention Enhancement

by Dongdong Huang, Dawei Xu and Yongjie Zhai

Sensors 2026, 26(4), 1291; https://doi.org/10.3390/s26041291 - 16 Feb 2026

Viewed by 497

Abstract

Road target detection is a crucial aspect of current research in automotive advanced driver assistance systems and intelligent transportation systems, where accuracy, speed, and lightweight design are key considerations. Compared to various sensors employed in driving assistance systems, millimeter-wave radar offers advantages such as all-weather operation, low hardware cost, strong penetration capability, and the ability to extract rich spatial information about targets. This paper tackles the challenges posed by the characteristics of Range-Angle map data from 77 GHz Frequency-Modulated Continuous Wave radar—namely, non-visible light imagery, abstract representation, rich fine details, and overlapping features. To this end, this paper proposes MMPFNet, a lightweight model based on the hypergraph mechanism with attention enhancement, as an extension of YOLOv13. First, an M-DSC3k2 module is proposed based on the hypergraph mechanism to enhance attention toward small targets. Second, a detection head with a double-bottleneck inverted MBConv-block structure is designed to improve the model’s accuracy and generalization capability. Third, a lightweight PPLConv module is customized to transform the backbone network, enhancing the model’s lightweight design while slightly reducing its accuracy. Considering the differences from traditional visible light datasets, the Focus Expansion-IoU loss function is introduced into the model to focus attention on different regression samples. The MMPFNet model achieves significant improvements in detecting common road targets such as pedestrians, bicycles, cars, and trucks on the Frequency-Modulated Continuous Wave radar Range-Angle dataset compared to the baseline YOLOv13n model: mAP50-95 increases by 16%, precision improves by 6%, and recall rises by 8.7%. MMPFNet is also evaluated on other non-visible light datasets such as CRUW-ONRD and soundprint datasets. Compared to commonly used detection models like FCOS and RetinaNet, MMPFNet achieves significant performance gains, attaining state-of-the-art results. Full article

(This article belongs to the Special Issue Microwave and Millimeter-Wave Sensing and Imaging on Wearable, Vehicular, and Portable Platforms)

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28 pages, 2690 KB

Open AccessArticle

Two-Dimensional Dynamic Logic Resource Allocation for Scalable RIS Channel Emulation

by Dan Fei, Haobo Zhang, Chen Chen, Hao Zhou, Peng Zheng, Guoyu Wang, Cheng Li, Jiayi Zhang, Zhaohui Song and Bo Ai

Sensors 2026, 26(3), 813; https://doi.org/10.3390/s26030813 - 26 Jan 2026

Viewed by 491

Abstract

This paper addresses the critical scalability challenge in Hardware-in-the-Loop (HIL) channel emulation for massive RIS-assisted 6G environments. We propose a Two-Dimensional Dynamic Logic Resource Allocation (2D-DLRA) architecture that decouples physical RF ports from baseband processing resources through hierarchical pooling at both the session level and the multipath level. By jointly virtualizing Logical Units (LUs) and Multipath Processing Units (MPUs), the proposed architecture overcomes the dual inefficiency of port underutilization and path-level sparsity inherent in conventional static designs. A rigorous analytical framework combining hierarchical queuing theory and non-cooperative game theory is developed to characterize system capacity, blocking probability, and user contention under heterogeneous workloads. Simulation results demonstrate that, under a strict QoS constraint of 1% blocking probability, the proposed 2D-DLRA architecture achieves a multi-fold increase in supported user capacity compared to static allocation with the same hardware resources. Moreover, for an end-to-end emulation error threshold of 3%, 91.8% of users meet the QoS requirement, compared to only 73.6% in static architectures. The results further show that dynamic pooling enables near-saturated hardware utilization, in contrast to the single-digit utilization typical of static designs in sparse RIS scenarios. These findings confirm that 2D-DLRA provides a scalable and hardware-efficient solution for large-scale RIS channel emulation, offering practical design guidelines for next-generation 6G HIL testing platforms. Full article

(This article belongs to the Special Issue Microwave and Millimeter-Wave Sensing and Imaging on Wearable, Vehicular, and Portable Platforms)

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13 pages, 7564 KB

Open AccessArticle

Microwave Fill Level Inspection System for Industrial Packaged Products

by Calin I. Maraloiu, Jorge A. Tobón Vasquez, Marco Ricci and Francesca Vipiana

Sensors 2025, 25(24), 7578; https://doi.org/10.3390/s25247578 - 13 Dec 2025

Viewed by 616

Abstract

Fill level control is one of the strict checks required when inspecting industrially packaged products. The purpose is both to ensure the content conformity according to the declared label information and to preserve the reliability of brand trust, strongly influenced by the customer’s evenness perception of the marketed items. To this aim, choosing the right technology is not an easy task: content and packaging material properties are essential to establish the suitability of a product to the fill level machine type. In this paper, we propose a novel approach, based on microwaves, to address this issue. The designed microwave inspection system consists of two Vivaldi antennas working between 1 and 18 GHz. We show its applicability to water, oil and alcohol-based products moving on conveyor belts at production speed. The performed experiments demonstrate good accuracy and efficiency of level classification and fault rejection in real-time processing. Full article

(This article belongs to the Special Issue Microwave and Millimeter-Wave Sensing and Imaging on Wearable, Vehicular, and Portable Platforms)

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