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Special Issue "Radar and Radiometric Sensors and Sensing"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors, Control, and Telemetry".

Deadline for manuscript submissions: closed (15 December 2019).

Special Issue Editors

Prof. Dr. Federico Alimenti
E-Mail Website
Guest Editor
Dipartimento d'Ingegneria, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy
Interests: RFID; RFID sensors; radar and radiometric sensors; green electronics; RF integrated circuits in CMOS and BiCMOS; SoC for IoT applications
Special Issues and Collections in MDPI journals
Prof. Stefania Bonafoni
E-Mail Website
Guest Editor
Dipartimento d'Ingegneria, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy
Interests: remote sensing of environment; urban heat Island; downscaling techniques; microwave radiometry from satellite and ground-based sensors; GNSS for atmospheric applicatons
Special Issues and Collections in MDPI journals
Prof. Paolo Mezzanotte
E-Mail Website
Guest Editor
Dipartimento d'Ingegneria, University of Perugia, via G. Duranti 93, 06125 Perugia, Italy
Tel. +39-075-585-3664; Fax: +39-075-585-3654
Interests: numerical methods and CAD techniques; microwave filters; design of microwave and millimeter–wave circuits; LTCC and RF-MEMS technologies; microwave circuits on cellulose; RFID; Wireless Power Transfer (WPT)
Special Issues and Collections in MDPI journals
Dr. Luca Roselli
E-Mail Website
Guest Editor
Associate Professor, Department of Engineering, University of Perugia, 06125 Perugia, Italy
Interests: applied electronics; high frequency electronics; RFID; printable circuits; green electronics; wireless power transfer (microwave transfer); IoT
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Radar and microwave radiometers are experiencing a new golden age thanks to the extreme miniaturization of electronics and the availability of transistors with a maximum oscillation frequency in excess to 300 GHz. As a consequence, small, light-weight, and low-cost radiometers are being designed or are already available in the market to cover unprecedented sensing applications, as required by the Internet of Things (IoT) paradigm. Automotive radars, drone-based radar and radiometric platforms, radars and radiometers for industrial and environmental monitoring are only a few examples of such a technological revolution.

This Special issue aims to bring together high-quality research and innovative development activities focused on sensor developments, sensing, and new application scenarios exploiting radars and microwave/mm-wave radiometers, including but not limited to:

  • new radar sensors;
  • new microwave/mm-wave radiometric sensors;
  • System-on-Chip radars or radiometers;
  • new antenna concepts for radar or radiometers;
  • new simulators for radar and radiometric imaging;
  • new measurement techniques for the characterization of radar or radiometers;
  • new algorithms for radar or radiometers data processing;
  • new sensing applications scenarios with radars or radiometers;
  • radar or radiometers for space-based applications and science;
  • applications of radar and radiometers in the IoT.

Both original research papers and review articles related to Radar and microwave/mm-wave sensors and sensing are solicited.

Prof. Federico Alimenti
Prof. Stefania Bonafoni
Prof. Paolo Mezzanotte
Prof. Luca Roselli
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 papers will be 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 2000 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.

Published Papers (6 papers)

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Research

Open AccessArticle
Joint Optimization of Transmit Waveform and Receive Filter with Pulse-to-Pulse Waveform Variations for MIMO GMTI
Sensors 2019, 19(24), 5575; https://doi.org/10.3390/s19245575 - 17 Dec 2019
Abstract
Multi-input multi-output (MIMO) is usually defined as a radar system in which the transmit time and receive time, space and transform domain can be separated into multiple independent signals. Given the bandwidth and power constraints of the radar system, MIMO radar can improve [...] Read more.
Multi-input multi-output (MIMO) is usually defined as a radar system in which the transmit time and receive time, space and transform domain can be separated into multiple independent signals. Given the bandwidth and power constraints of the radar system, MIMO radar can improve its performance by optimize design transmit waveforms and receive filters, so as to achieve better performance in suppressing clutter and noise. In this paper, we cyclicly optimize the transmit waveform and receive filters, so as to maximize the output signal interference and noise ratio (SINR). From fixed pulse-to-pulse waveform to pulse-to-pulse waveform variations, we discuss the joint optimization under energy constraint, then extend it to optimizations under constant-envelope constraint and similarity constraint. Compared to optimization with fixed pulse-to-pulse waveform, the generalized optimization achieves higher output SINR and lower minimum detectable velocity (MDV), further improve the suppressing performance. Full article
(This article belongs to the Special Issue Radar and Radiometric Sensors and Sensing)
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Open AccessArticle
Review-Microwave Radar Sensing Systems for Search and Rescue Purposes
Sensors 2019, 19(13), 2879; https://doi.org/10.3390/s19132879 - 28 Jun 2019
Abstract
This paper presents a survey of recent developments using Doppler radar sensor in searching and locating an alive person under debris or behind a wall. Locating a human and detecting the vital signs such as breathing rate and heartbeat using a microwave sensor [...] Read more.
This paper presents a survey of recent developments using Doppler radar sensor in searching and locating an alive person under debris or behind a wall. Locating a human and detecting the vital signs such as breathing rate and heartbeat using a microwave sensor is a non-invasive technique. Recently, many hardware structures, signal processing approaches, and integrated systems have been introduced by researchers in this field. The purpose is to enhance the accuracy of vital signs’ detection and location detection and reduce energy consumption. This work concentrates on the representative research on sensing systems that can find alive people under rubble when an earthquake or other disasters occur. In this paper, various operating principles and system architectures for finding survivors using the microwave radar sensors are reviewed. A comparison between these systems is also discussed. Full article
(This article belongs to the Special Issue Radar and Radiometric Sensors and Sensing)
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Open AccessArticle
OFDM Chirp Waveform Design Based on Subchirp Bandwidth Overlap and Segmented Transmitting for Low Correlation Interference in MIMO Radar
Sensors 2019, 19(12), 2696; https://doi.org/10.3390/s19122696 - 14 Jun 2019
Abstract
There are some special merits for the orthogonal frequency division multiplexing (OFDM) chirp waveform as multiple input multiple output (MIMO) signals. This signal has high range resolution, good Doppler tolerance, and constant modulus superiority since it exploits a full bandwidth and is based [...] Read more.
There are some special merits for the orthogonal frequency division multiplexing (OFDM) chirp waveform as multiple input multiple output (MIMO) signals. This signal has high range resolution, good Doppler tolerance, and constant modulus superiority since it exploits a full bandwidth and is based on chirp signals. The correlation sidelobe peaks level are critical for the detection requirement of MIMO radar signals, however conventional OFDM chirp signals produce high autocorrelation sidelobe peaks (ASP) and cross-correlation peaks (CP), which reduces detection performance. In this paper, we explore the structure of OFDM chirp signals’ autocorrelation function and proposed a scheme to reduce the designed signal’s ASP by a designing suitable range of subchirp bandwidth and a segmented transmit-receive mode. Next, we explore a suitable range of interval between the chirp rates of each two signals to reduce the CP. The simulation of designed signals verifies the effectiveness of the proposed methods in the reduction of ASP and CP, with the correlation performance being compared with recent relate studies. In addition, the multiple signals detection and one-dimensional range image simulation show the good detection performance of a designed signal in MIMO radar detection. Full article
(This article belongs to the Special Issue Radar and Radiometric Sensors and Sensing)
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Open AccessArticle
A 1-GHz 64-Channel Cross-Correlation System for Real-Time Interferometric Aperture Synthesis Imaging
Sensors 2019, 19(7), 1739; https://doi.org/10.3390/s19071739 - 11 Apr 2019
Cited by 1
Abstract
We present a 64-channel 1-bit/2-level cross-correlation system for a passive millimeter wave imager used for indoor human body security screening. Sixty-four commercial comparators are used to perform 1-bit analog-to-digital conversion, and a Field Programmable Gate Array (FPGA) is used to perform the cross-correlation [...] Read more.
We present a 64-channel 1-bit/2-level cross-correlation system for a passive millimeter wave imager used for indoor human body security screening. Sixty-four commercial comparators are used to perform 1-bit analog-to-digital conversion, and a Field Programmable Gate Array (FPGA) is used to perform the cross-correlation processing. This system can handle 2016 cross-correlations at the sample frequency of 1GHz, and its power consumption is 48.75 W. The data readout interface makes it possible to read earlier data while simultaneously performing the next correlation when imaging at video rate. The longest integration time is up to 68.7 s, which can satisfy the requirements of video rate imaging and system calibration. The measured crosstalk between neighboring channels is less than 0.068%, and the stability is longer than 10 s. A correlation efficiency greater than 96% is achieved for input signal levels greater than −25 dBm. Full article
(This article belongs to the Special Issue Radar and Radiometric Sensors and Sensing)
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Open AccessArticle
On the Use of Microwave Holography to Detect Surface Defects of Rails and Measure the Rail Profile
Sensors 2019, 19(6), 1376; https://doi.org/10.3390/s19061376 - 19 Mar 2019
Cited by 1
Abstract
The use of microwave holography for detecting rail surface defects is considered in this paper. A brief review of available sources on radar methods for detecting defects on metal surfaces and rails is given. An experimental setup consisting of a two-coordinate electromechanical scanner [...] Read more.
The use of microwave holography for detecting rail surface defects is considered in this paper. A brief review of available sources on radar methods for detecting defects on metal surfaces and rails is given. An experimental setup consisting of a two-coordinate electromechanical scanner and a radar with stepped frequency signal in the range from 22.2 to 26.2 GHz is described, with the help of which experimental data were obtained. Fragments of R24 rails with surface defects in their heads were used as the object of study. The radar images of rail defects were obtained by the described method based on back propagation of a wavefront. It is shown that polarization properties of electromagnetic waves can be used to increase the contrast of small-scale surface defects. A method of estimating rail surface profile by radar measurements is given and applied to the experimental data. Comparison of the longitudinal rail head profiles obtained by radar and by direct contact measurements showed that the radar method gives comparable accuracy. Full article
(This article belongs to the Special Issue Radar and Radiometric Sensors and Sensing)
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Open AccessArticle
Statistical Approach to Spectrogram Analysis for Radio-Frequency Interference Detection and Mitigation in an L-Band Microwave Radiometer
Sensors 2019, 19(2), 306; https://doi.org/10.3390/s19020306 - 14 Jan 2019
Abstract
For the elimination of radio-frequency interference (RFI) in a passive microwave radiometer, the threshold level is generally calculated from the mean value and standard deviation. However, a serious problem that can arise is an error in the retrieved brightness temperature from a higher [...] Read more.
For the elimination of radio-frequency interference (RFI) in a passive microwave radiometer, the threshold level is generally calculated from the mean value and standard deviation. However, a serious problem that can arise is an error in the retrieved brightness temperature from a higher threshold level owing to the presence of RFI. In this paper, we propose a method to detect and mitigate RFI contamination using the threshold level from statistical criteria based on a spectrogram technique. Mean and skewness spectrograms are created from a brightness temperature spectrogram by shifting the 2-D window to discriminate the form of the symmetric distribution as a natural thermal emission signal. From the remaining bins of the mean spectrogram eliminated by RFI-flagged bins in the skewness spectrogram for data captured at 0.1-s intervals, two distribution sides are identically created from the left side of the distribution by changing the standard position of the distribution. Simultaneously, kurtosis calculations from these bins for each symmetric distribution are repeatedly performed to determine the retrieved brightness temperature corresponding to the closest kurtosis value of three. The performance is evaluated using experimental data, and the maximum error and root-mean-square error (RMSE) in the retrieved brightness temperature are served to be less than approximately 3 K and 1.7 K, respectively, from a window with a size of 100 × 100 time–frequency bins according to the RFI levels and cases. Full article
(This article belongs to the Special Issue Radar and Radiometric Sensors and Sensing)
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