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Radar for Environmental Sensing
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Radar for Environmental Sensing

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

Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 10802

Special Issue Editors

Dr. Danilo Orlando

E-Mail Website
Guest Editor
Department of Engineering, University of Niccolo Cusano, Via Don Carlo Gnocchi 3, 00166 Rome, Italy
Interests: the field of statistical signal processing with applications to radar and sonar
Special Issues, Collections and Topics in MDPI journals
Dr. Pia Addabbo

E-Mail Website
Guest Editor
Department of Telecommunication Engineering, University of Study “Giustino Fortunato”, 82100 Benevento, Italy
Interests: statistical signal processing; image processing; passive remote sensing (hyperspectral sensor); active remote sensing (radar, SAR, GNSS-R)
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Radar systems are ubiquitous and enjoy endless technological advancements that continuously lead to enhanced miniaturization, digitalization, and very high computational performance. Moreover, growing demands for better performance and an increased number of radar applications call for wider bandwidths, possibly generating conflicts with the bandwidth demand from communication systems. In addition, such scenarios become more challenging due to intentional interference generated by low-cost but powerful devices. Therefore, it is of primary importance to conceive systems capable of guaranteeing reliable detection/estimation performance in such complex scenarios. In this respect, this Special Issue aims to collect the most recent contributions in the field of environmental sensing related to sensor-based processing algorithms, sensor design, and system design.

Dr. Danilo Orlando
Dr. Pia Addabbo
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

  • radar-communications coexistence
  • machine learning-based systems
  • passive location
  • detection in spectrally crowded scenarios
  • target/interference classification
  • electronic countermeasures
  • smart beamforming
  • RIS-aided systems

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Published Papers (4 papers)

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Research

19 pages, 5425 KiB  
Article
A Low-Cost Radar-Based IoT Sensor for Noncontact Measurements of Water Surface Velocity and Depth
by Stephen Catsamas, Baiqian Shi, Miao Wang, Jieren Xiao, Peter Kolotelo and David McCarthy
Sensors 2023, 23(14), 6314; https://doi.org/10.3390/s23146314 - 11 Jul 2023
Cited by 3 | Viewed by 4522
Abstract
We designed an out-of-water radar water velocity and depth sensor, which is unique due to its low cost and low power consumption. The sensor is a first at a cost of less than USD 50, which is well suited to previously cost-prohibited high-resolution [...] Read more.
We designed an out-of-water radar water velocity and depth sensor, which is unique due to its low cost and low power consumption. The sensor is a first at a cost of less than USD 50, which is well suited to previously cost-prohibited high-resolution monitoring schemes. This use case is further supported by its out-of-water operation, which provides low-effort installations and longer maintenance-free intervals when compared with in-water sensors. The inclusion of both velocity and depth measurement capabilities allows the sensor to also be used as an all-in-one solution for flowrate measurement. We discuss the design of the sensor, which has been made freely available under open-hardware and open-source licenses. The design uses commonly available electronic components, and a 3D-printed casing makes the design easy to replicate and modify. Not before seen on a hydrology sensor, we include a 3D-printed radar lens in the casing, which boosts radar sensitivity by 21 dB. The velocity and depth-sensing performance were characterised in laboratory and in-field tests. The depth is accurate to within ±6% and ±7 mm and the uncertainty in the velocity measurements ranges from less than 30% to 36% in both laboratory and field conditions. Our sensor is demonstrated to be a feasible low-cost design which nears the uncertainty of current, yet more expensive, velocity sensors, especially when field performance is considered. Full article
(This article belongs to the Special Issue Radar for Environmental Sensing)
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22 pages, 9950 KiB  
Article
Cloud and Precipitation Profiling Radars: The First Combined W- and K-Band Radar Profiler Measurements in Italy
by Mario Montopoli, Alessandro Bracci, Elisa Adirosi, Marco Iarlori, Saverio Di Fabio, Raffaele Lidori, Andrea Balotti, Luca Baldini and Vincenzo Rizi
Sensors 2023, 23(12), 5524; https://doi.org/10.3390/s23125524 - 12 Jun 2023
Cited by 1 | Viewed by 1665
Abstract
Clouds cover substantial parts of the Earth’s surface and they are one of the most essential components of the global climate system impacting the Earth’s radiation balance as well as the water cycle redistributing water around the globe as precipitation. Therefore, continuous observation [...] Read more.
Clouds cover substantial parts of the Earth’s surface and they are one of the most essential components of the global climate system impacting the Earth’s radiation balance as well as the water cycle redistributing water around the globe as precipitation. Therefore, continuous observation of clouds is of primary interest in climate and hydrological studies. This work documents the first efforts in Italy in remote sensing clouds and precipitation using a combination of K- and W-band (24 and 94 GHz, respectively) radar profilers. Such a dual-frequency radar configuration has not been widely used yet, but it could catch on in the near future given its lower initial cost and ease of deployment for commercially available systems at 24 GHz, with respect to more established configurations. A field campaign running at the Casale Calore observatory at the University of L’Aquila, Italy, nestled in the Apennine mountain range is described. The campaign features are preceded by a review of the literature and the underpinning theoretical background that might help newcomers, especially in the Italian community, to approach cloud and precipitation remote sensing. This activity takes place in interesting time for radar sensing clouds and precipitation, stimulated both by the launch of the ESA/JAXA EarthCARE satellite missions scheduled in 2024, which will have on-board, among other instruments, a W-band Doppler cloud radar and the proposal of new missions using cloud radars currently undergoing their feasibility studies (e.g., WIVERN and AOS in Europe and Canada, and U.S., respectively). Full article
(This article belongs to the Special Issue Radar for Environmental Sensing)
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31 pages, 12438 KiB  
Article
A Flexible Design Strategy for Three-Element Non-Uniform Linear Arrays
by Andrea Quirini, Francesca Filippini, Carlo Bongioanni, Fabiola Colone and Pierfrancesco Lombardo
Sensors 2023, 23(10), 4872; https://doi.org/10.3390/s23104872 - 18 May 2023
Cited by 1 | Viewed by 1436
Abstract
This paper illustrates a flexible design strategy for a three-element non-uniform linear array (NULA) aimed at estimating the direction of arrival (DoA) of a source of interest. Thanks to the spatial diversity resulting from non-uniform sensor spacings, satisfactory DoA estimation accuracies can be [...] Read more.
This paper illustrates a flexible design strategy for a three-element non-uniform linear array (NULA) aimed at estimating the direction of arrival (DoA) of a source of interest. Thanks to the spatial diversity resulting from non-uniform sensor spacings, satisfactory DoA estimation accuracies can be achieved by employing a very limited number of receiving elements. This makes NULA configurations particularly attractive for low-cost passive location applications. To estimate the DoA of the source of interest, we resort to the maximum likelihood estimator, and the proposed design strategy is obtained by constraining the maximum pairwise error probability to control the errors occurring due to outliers. In fact, it is well known that the accuracy of the maximum likelihood estimator is often degraded by outliers, especially when the signal-to-noise power ratio does not belong to the so-called asymptotic region. The imposed constraint allows for the defining of an admissible region in which the array should be selected. This region can be further modified to incorporate practical design constraints concerning the antenna element size and the positioning accuracy. The best admissible array is then compared to the one obtained with a conventional NULA design approach, where only antenna spacings multiple of λ/2 are considered, showing improved performance, which is also confirmed by the experimental results. Full article
(This article belongs to the Special Issue Radar for Environmental Sensing)
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18 pages, 23371 KiB  
Article
A Speedy Point Cloud Registration Method Based on Region Feature Extraction in Intelligent Driving Scene
by Deli Yan, Weiwang Wang, Shaohua Li, Pengyue Sun, Weiqi Duan and Sixuan Liu
Sensors 2023, 23(9), 4505; https://doi.org/10.3390/s23094505 - 5 May 2023
Cited by 1 | Viewed by 2385
Abstract
The challenges of point cloud registration in intelligent vehicle driving lie in the large scale, complex distribution, high noise, and strong sparsity of lidar point cloud data. This paper proposes an efficient registration algorithm for large-scale outdoor road scenes by selecting the continuous [...] Read more.
The challenges of point cloud registration in intelligent vehicle driving lie in the large scale, complex distribution, high noise, and strong sparsity of lidar point cloud data. This paper proposes an efficient registration algorithm for large-scale outdoor road scenes by selecting the continuous distribution of key area laser point clouds as the registration point cloud. The algorithm extracts feature descriptions of the key point cloud and introduces local geometric features of the point cloud to complete rough and fine registration under constraints of key point clouds and point cloud features. The algorithm is verified through extensive experiments under multiple scenarios, with an average registration time of 0.5831 s and an average accuracy of 0.06996 m, showing significant improvement compared to other algorithms. The algorithm is also validated through real-vehicle experiments, demonstrating strong versatility, reliability, and efficiency. This research has the potential to improve environment perception capabilities of autonomous vehicles by solving the point cloud registration problem in large outdoor scenes. Full article
(This article belongs to the Special Issue Radar for Environmental Sensing)
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