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Electronics
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Intelligent Radar Platform Technology for Smart Environments
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Intelligent Radar Platform Technology for Smart Environments

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 7302

Special Issue Editor

Prof. Dr. Han Lim Lee

E-Mail Website
Guest Editor
School of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, Korea
Interests: mmWave applications; RF circuits and systems; antennas; microwave sensors and RFIC/MMIC
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the advance of the Internet of Things (IoT) and the Internet of Everything (IoE), the integration of smart devices and big data with everyday objects in peoples’ lives currently brings a rapid momentum to smart environments. To maintain a continuous and efficient interaction between physical world and computational data, an intelligent radar platform technology must be supported and accompanied by solving new challenges that hinder the full potential of sensor-based environments. A successful adoption of intelligent radars toward smart environments can only be possible through technical convergence in wireless communication, sensor devices, advanced signal/image processing, network, system architecture, artificial intelligence, etc. To drive the optimal operation of radar intelligence through the platform technology for various environments, this Special Issue invites submissions of technical papers that may address but are not limited to the topics below:

  • Radar architectures: FMCW, PMCW, UWB, SIMO, MIMO, analog beamforming, all-digital beamforming, hybrid beamforming, etc.
  • Circuits and system: low-noise receiver, high efficiency transmitter, TX leakage cancellation, multi-channel transceiver, signal and waveform generator, etc.
  • Radar signal processing: machine-learning based algorithm, AI-based applications, etc.
  • Sensor applications for smart environments: automotive sensors, infrastructure sensors, UAV sensors, motion sensors, bio- and medical sensors, etc.
  • Wearable devices and self-powered sensor: energy harvesting, flexible sensors, etc.
  • Smart antenna and antenna array: beamforming antenna, pattern reconfigurable antenna, polarization diversity, on-chip antenna, flexible antenna, etc.

Prof. Dr. Han Lim Lee
Guest Editor

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. Electronics 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 2400 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

  • radar sensor
  • intelligent radar
  • smart environment
  • smart sensor
  • radar platform
  • radar signal processing
  • radar transceiver
  • smart antenna
  • beamformig

Published Papers (3 papers)

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Research

11 pages, 1224 KiB  
Article
MM-Wave Radar-Based Recognition of Multiple Hand Gestures Using Long Short-Term Memory (LSTM) Neural Network
by Piotr Grobelny and Adam Narbudowicz
Electronics 2022, 11(5), 787; https://doi.org/10.3390/electronics11050787 - 3 Mar 2022
Cited by 5 | Viewed by 3099
Abstract
The paper proposes a simple machine learning solution for hand-gesture classification, based on processed MM-wave radar signal. It investigates the classification up to 12 different intuitive and ergonomic gestures, which are intended to serve as a contactless user interface. The system is based [...] Read more.
The paper proposes a simple machine learning solution for hand-gesture classification, based on processed MM-wave radar signal. It investigates the classification up to 12 different intuitive and ergonomic gestures, which are intended to serve as a contactless user interface. The system is based on AWR1642 boost Frequency-Modulated Continuous-Wave (FMCW) radar, which allows capturing standardized data to support the scalability of the proposed solution. More than 4000 samples were collected from 4 different people, with all signatures extracted from the radar hardware available in open-access database accompanying the publication. Collected data were processed and used to train Long short-term memory (LSTM) and artificial recurrent neural network (RNN) architecture. The work studies the impact of different input parameters, the number of hidden layers, and the number of neurons in those layers. The proposed LSTM network allows for classification of different gestures, with the total accuracy ranging from 94.4% to 100% depending on use-case scenario, with a relatively small architecture of only 2 hidden layers with 32 neurons in each. The solution is also tested with additional data recorded from subjects not involved in the original training set, resulting in an accuracy drop of no more than 2.24%. This demonstrates that the proposed solution is robust and scalable, allowing quick and reliable creation of larger databases of gestures to expand the use of machine learning with radar technologies. Full article
(This article belongs to the Special Issue Intelligent Radar Platform Technology for Smart Environments)
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11 pages, 519 KiB  
Article
Enhancement of Radar Detection Accuracy Using H-Beam Wave Polarization in Random Media
by Hosam El-Ocla
Electronics 2021, 10(22), 2804; https://doi.org/10.3390/electronics10222804 - 16 Nov 2021
Viewed by 1119
Abstract
This work addresses the range in which the accuracy of object identification is enhanced regardless of radar parameters. We compute the radar cross-section (RCS) of conducting objects in free space and random media. We use beam wave incidence and postulate its coherency with [...] Read more.
This work addresses the range in which the accuracy of object identification is enhanced regardless of radar parameters. We compute the radar cross-section (RCS) of conducting objects in free space and random media. We use beam wave incidence and postulate its coherency with a finite width around an object located in the far field. Accordingly, we examine the impact of radar parameters on the RCS, where these parameters include the incident angle, target size and complexity, medium fluctuation intensity and the beam size of the incident waves. H-wave polarization is assumed for the waves’ incidence. Full article
(This article belongs to the Special Issue Intelligent Radar Platform Technology for Smart Environments)
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16 pages, 7832 KiB  
Article
W-band MIMO GB-SAR for Bridge Testing/Monitoring
by Lapo Miccinesi, Tommaso Consumi, Alessandra Beni and Massimiliano Pieraccini
Electronics 2021, 10(18), 2261; https://doi.org/10.3390/electronics10182261 - 14 Sep 2021
Cited by 17 | Viewed by 2478
Abstract
Interferometric radars are widely used for static and dynamic monitoring of large structures such as bridges, culverts, wind turbine towers, chimneys, masonry towers, stay cables, buildings, and monuments. Most of these radars operate in Ku-band (17 GHz). Nevertheless, a higher operative frequency could [...] Read more.
Interferometric radars are widely used for static and dynamic monitoring of large structures such as bridges, culverts, wind turbine towers, chimneys, masonry towers, stay cables, buildings, and monuments. Most of these radars operate in Ku-band (17 GHz). Nevertheless, a higher operative frequency could allow the design of smaller, lighter, and faster equipment. In this paper, a fast MIMO-GBSAR (Multiple-Input Multiple-Output Ground-Based Synthetic Aperture Radar) operating in W-band (77 GHz) has been proposed. The radar can complete a scan in less than 8 s. Furthermore, as its overall dimension is smaller than 230 mm, it can be easily fixed to the head of a camera tripod, which makes its deployment in the field very easy, even by a single operator. The performance of this radar was tested in a controlled environment and in a realistic case study. Full article
(This article belongs to the Special Issue Intelligent Radar Platform Technology for Smart Environments)
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