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Advances in Doppler and FMCW Radar Sensors
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Advances in Doppler and FMCW Radar Sensors

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

Deadline for manuscript submissions: 31 May 2024 | Viewed by 6496

Special Issue Editors

Dr. Roberto Vincenti Gatti

E-Mail Website1 Website2
Guest Editor
Department of Engineering, University of Perugia, Perugia, Italy
Interests: slotted waveguide arrays; phased arrays; reflectarrays; radar systems; satcom systems
Special Issues, Collections and Topics in MDPI journals
Dr. Federico Alimenti

E-Mail Website
Guest Editor
Dipartimento d'Ingegneria, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy
Interests: radar and radiometric sensors; high data-rate transceivers; microwave electronic circuits; power amplifiers for wireless communications; RFID systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Doppler and frequency-modulated continuous wave (FMCW) radar sensors are powerful tools that have been widely used in various applications. They provide high accuracy, reliability, and robustness in detecting and tracking moving targets, and their potential has expanded even further with recent advancements in signal processing techniques, radar architectures, beam steering antennas, and system design.

Doppler and FMCW radar sensors are unique in their ability to provide continuous, real-time sensing of moving targets, making them invaluable in applications such as automotive sensing for adaptive cruise control, collision avoidance, and parking assistance, medical sensing for vital signs monitoring and gesture recognition, and environmental sensing for object detection, tracking, and monitoring.

This Special Issue on "Advances in Doppler and FMCW Radar Sensors" aims to provide a comprehensive overview of the latest developments and innovations in this field, including their theory, design, and applications. The scope of this Special Issue covers a wide range of topics related to Doppler and FMCW radar sensors, including signal processing techniques, innovative radar architectures and system designs, innovative technologies and architectures for beam steering antennas, and applications in fields such as automotive, medical, and environmental sensing. The articles presented in this Special Issue are expected to provide a thorough understanding of the state of the art in this topic, and to highlight future research directions.

By bringing together the latest research and advancements in this area, this Special Issue is expected to serve as a valuable resource for researchers, engineers, and practitioners working in the field of radar sensing. The insights presented in this Special Issue will enable Doppler and FMCW radar sensors to be used in even more applications, and will ultimately help improve the accuracy, reliability, and robustness of these sensors, making them an even more indispensable tool for sensing moving targets.

Dr. Roberto Vincenti Gatti
Dr. Federico Alimenti
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 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • Doppler radar
  • FMCW radar
  • signal processing
  • radar systems
  • radar architectures
  • beam steering antennas
  • automotive sensing
  • medical sensing
  • environmental sensing

Published Papers (4 papers)

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Research

16 pages, 7548 KiB  
Article
Robust Hand Gesture Recognition Using a Deformable Dual-Stream Fusion Network Based on CNN-TCN for FMCW Radar
by Meiyi Zhu, Chaoyi Zhang, Jianquan Wang, Lei Sun and Meixia Fu
Sensors 2023, 23(20), 8570; https://doi.org/10.3390/s23208570 - 19 Oct 2023
Viewed by 1604
Abstract
Hand Gesture Recognition (HGR) using Frequency Modulated Continuous Wave (FMCW) radars is difficult because of the inherent variability and ambiguity caused by individual habits and environmental differences. This paper proposes a deformable dual-stream fusion network based on CNN-TCN (DDF-CT) to solve this problem. [...] Read more.
Hand Gesture Recognition (HGR) using Frequency Modulated Continuous Wave (FMCW) radars is difficult because of the inherent variability and ambiguity caused by individual habits and environmental differences. This paper proposes a deformable dual-stream fusion network based on CNN-TCN (DDF-CT) to solve this problem. First, we extract range, Doppler, and angle information from radar signals with the Fast Fourier Transform to produce range-time (RT) and range-angle (RA) maps. Then, we reduce the noise of the feature map. Subsequently, the RAM sequence (RAMS) is generated by temporally organizing the RAMs, which captures a target’s range and velocity characteristics at each time point while preserving the temporal feature information. To improve the accuracy and consistency of gesture recognition, DDF-CT incorporates deformable convolution and inter-frame attention mechanisms, which enhance the extraction of spatial features and the learning of temporal relationships. The experimental results show that our method achieves an accuracy of 98.61%, and even when tested in a novel environment, it still achieves an accuracy of 97.22%. Due to its robust performance, our method is significantly superior to other existing HGR approaches. Full article
(This article belongs to the Special Issue Advances in Doppler and FMCW Radar Sensors)
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18 pages, 32027 KiB  
Article
A Low-Complexity Hand Gesture Recognition Framework via Dual mmWave FMCW Radar System
by Yinzhe Mao, Lou Zhao, Chunshan Liu and Minhao Ling
Sensors 2023, 23(20), 8551; https://doi.org/10.3390/s23208551 - 18 Oct 2023
Cited by 1 | Viewed by 1028
Abstract
In this paper, we propose a novel low-complexity hand gesture recognition framework via a multiple Frequency Modulation Continuous Wave (FMCW) radar-based sensing system. In this considered system, two radars are deployed distributively to acquire motion vectors from different observation perspectives. We first independently [...] Read more.
In this paper, we propose a novel low-complexity hand gesture recognition framework via a multiple Frequency Modulation Continuous Wave (FMCW) radar-based sensing system. In this considered system, two radars are deployed distributively to acquire motion vectors from different observation perspectives. We first independently extract reflection points of the interested target from different radars by applying the proposed neighboring reflection points detection method after processing the traditional 2-dimensional Fast Fourier Transform (2D-FFT). The obtained sufficient corresponding information of detected reflection points, e.g., distances, velocities, and angle information, can be exploited to synthesize motion velocity vectors to achieve a high signal-to-noise ratio (SNR) performance, which does not require knowledge of the relative position of the two radars. Furthermore, we utilize a long short-term memory (LSTM) network as well as the synthesized motion velocity vectors to classify different gestures, which can achieve a significantly high accuracy of gesture recognition with a 1600-sample data set, e.g., 98.0%. The experimental results also illustrate the robustness of the proposed gesture recognition systems, e.g., changing the environment background and adding new gesture performers. Full article
(This article belongs to the Special Issue Advances in Doppler and FMCW Radar Sensors)
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19 pages, 6048 KiB  
Article
FMCW Radar System Interference Mitigation Based on Time-Domain Signal Reconstruction
by Zhengguang Xu and Shanyong Wei
Sensors 2023, 23(16), 7113; https://doi.org/10.3390/s23167113 - 11 Aug 2023
Cited by 1 | Viewed by 1573
Abstract
In this study, an interference detection and mitigation method is proposed for frequency-modulated continuous-wave radar systems based on time-domain signal reconstruction. The interference detection method uses the difference in one-dimensional fast Fourier transform (1D-FFT) results between targets and interferences. In the 1D-FFT results, [...] Read more.
In this study, an interference detection and mitigation method is proposed for frequency-modulated continuous-wave radar systems based on time-domain signal reconstruction. The interference detection method uses the difference in one-dimensional fast Fourier transform (1D-FFT) results between targets and interferences. In the 1D-FFT results, the target appears as a peak at the same frequency point for all chirps within one frame, whereas the interference appears as the absence of target peaks within the first or last few chirps within one frame or as a shift in the target peak position in different chirps. Then, the interference mitigation method reconstructs the interference signal in the time domain by the estimated parameter from the 1D-FFT results, so the interference signal can be removed from the time domain without affecting the target signal. The simulation results show that the proposed interference mitigation algorithm can reduce the amplitude of interference by about 25 dB. The experimental results show that the amplitude of interference is reduced by 20–25 dB, proving the effectiveness of the simulation results. Full article
(This article belongs to the Special Issue Advances in Doppler and FMCW Radar Sensors)
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16 pages, 5410 KiB  
Article
Remote Estimation of Blood Pressure Using Millimeter-Wave Frequency-Modulated Continuous-Wave Radar
by Lovedeep Singh, Sungjin You, Byung Jang Jeong, Chiwan Koo and Youngwook Kim
Sensors 2023, 23(14), 6517; https://doi.org/10.3390/s23146517 - 19 Jul 2023
Viewed by 1693
Abstract
This paper proposes to remotely estimate a human subject’s blood pressure using a millimeter-wave radar system. High blood pressure is a critical health threat that can lead to diseases including heart attacks, strokes, kidney disease, and vision loss. The commonest method of measuring [...] Read more.
This paper proposes to remotely estimate a human subject’s blood pressure using a millimeter-wave radar system. High blood pressure is a critical health threat that can lead to diseases including heart attacks, strokes, kidney disease, and vision loss. The commonest method of measuring blood pressure is based on a cuff that is contact-based, non-continuous, and cumbersome to wear. Continuous remote monitoring of blood pressure can facilitate early detection and treatment of heart disease. This paper investigates the possibility of using millimeter-wave frequency-modulated continuous-wave radar to measure the heart blood pressure by means of pulse wave velocity (PWV). PWV is known to be highly correlated with blood pressure, which can be measured by pulse transit time. We measured PWV using a two-millimeter wave radar focused on the subject’s chest and wrist. The measured time delay provided the PWV given the length from the chest to the wrist. In addition, we analyzed the measured radar signal from the wrist because the shape of the pulse wave purveyed information on blood pressure. We investigated the area under the curve (AUC) as a feature and found that AUC is strongly correlated with blood pressure. In the experiment, five human subjects were measured 50 times each after performing different activities intended to influence blood pressure. We used artificial neural networks to estimate systolic blood pressure (SBP) and diastolic blood pressure (SBP) with both PWV and AUC as inputs. The resulting root mean square errors of estimated blood pressure were 3.33 mmHg for SBP and 3.14 mmHg for DBP. Full article
(This article belongs to the Special Issue Advances in Doppler and FMCW Radar Sensors)
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