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Recent Advancements in Radar Imaging and Sensing Technology II

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

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 6699

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Special Issue Editors

Prof. Dr. Piotr Samczynski

E-Mail Website1 Website2
Guest Editor

Politechnika Warszawska, Warsaw University of Technology, 00-661 Warszawa, Poland
Interests: SAR/ISAR; passive radars; passive SAR/ISAR; noise radars; radar signal processing
Special Issues, Collections and Topics in MDPI journals

Dr. Elisa Giusti

E-Mail Website
Guest Editor

National Laboratory of Radar and Surveillance Systems (RaSS), CNIT (National Inter-University Consortium for Telecommunications), Pisa, Italy
Interests: radar imaging tecniques; Inverse synthetic aperture radar (ISAR); interferometric ISAR (InISAR); radar polarimetry; ATR by using radar images
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

For the last few decades, radar imaging and sensing technology have made major scientific and technical progress. The first applications of this technology were devoted mainly to military users. Currently, radar imaging and sensing techniques are widely used in many civilian applications, from medicine and security, to safety assistance sensors widely used in transportation, including cars, trains, and airplanes. These technologies are beginning to be all around us.

With the fast development of new hardware platforms with advanced computational resources, which are widely available on the market, novel signal processing techniques—enabling enhanced functionalities of the radar systems—have been implemented. This, in turn, makes it possible to apply new technology in radar imaging as, for example, passive radar sensing. Just a few years ago, this type of sensing was at a very low technical readiness level, and today it has become a mature technology that will probably be offered on the market within the next few years. Moreover, the ever-wider bandwidth of the currently available receivers allows us to obtain very high resolution radar images, utilizing both the active and passive radar technology.

This Special Issue aims to gather the latest research results in modern radar technology using active and/or radar imaging sensing techniques in various applications, including both military use and a broad spectrum of civilian applications. The contributions from leading experts in this research field will be collected and presented in this special journal issue.

This Special Issue aims to highlight the advances in radar imaging and sensing technology. Topics include, but are not limited, to:

High Resolution Radar Imaging;
Novel SAR and ISAR Imaging Techniques;
Passive Radar Imaging Technology;
New Techniques in Radar Signal Processing;
Modern Civilian Applications of using Radar Technology for Sensing;
Multiband and/or Multistatic Radar Imaging;
Novel Fusion Techniques in Radar Technology;
Multiband and/or Multistatic Radar Sensing;
Multifunction Radar Sensing.

This special edition is the 2nd edition of the very successful Special Issue held in the past. The contributions from the previous edition can be found at the following website:

Sensors | Special Issue: Recent Advancements in Radar Imaging and Sensing Technology (mdpi.com)

We encourage all researchers working in the field to submit their recent research results in the latest edition of the Special Issue on Recent Advancements in Radar Imaging and Sensing Technology.

Prof. Dr. Piotr Samczynski
Dr. Elisa Giusti
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 Signal Processing
Radar Imaging
SAR
ISAR
PCL
PBR
ATR
NCTR
Multiband Processing
Multistatic Processing
Multistatic Radar Imaging
Multifunction Radar
Modern Radar Applications

Related Special Issue

Recent Advancements in Radar Imaging and Sensing Technology in Sensors (20 articles)

Published Papers (6 papers)

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Research

15 pages, 5731 KiB

Open AccessArticle

A General Scheme of a Branch-and-Bound Approach for the Sensor Selection Problem in Near-Field Broadband Beamforming

by Agnieszka Wielgus and Bogusław Szlachetko

Sensors 2024, 24(2), 470; https://doi.org/10.3390/s24020470 - 12 Jan 2024

Viewed by 429

Abstract

This paper is devoted to the sensor selection problem. A broadband receiver beamforming working in a near-field is considered. The system response should be as close as possible to the desired one, which is optimized in the sense of

L_{2}

norm. The [...] Read more.

L_{2}

norm. The problem considered is at least NP-hard. Therefore, the branch-and-bound algorithm is developed to solve the problem. The proposed approach is universal and can be applied not only to microphone arrays but also to antenna arrays; that is, the methodology for the generation of consecutive solutions can be applied to different types of sensor selection problems. Next, for a larger microphone array, an efficient metaheuristic algorithm is constructed. The algorithm implemented is a hybrid genetic algorithm based on the ITÖ process. Numerical experiments show that the proposed approach can be successfully applied to the sensor selection problem. Full article

(This article belongs to the Special Issue Recent Advancements in Radar Imaging and Sensing Technology II)

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Figure 1

19 pages, 1802 KiB

Open AccessArticle

Real Aperture Radar Super-Resolution Imaging for Sea Surface Monitoring Based on a Hybrid Model

by Ke Tan, Shengqi Zhou, Xingyu Lu, Jianchao Yang, Weimin Su and Hong Gu

Sensors 2023, 23(23), 9609; https://doi.org/10.3390/s23239609 - 04 Dec 2023

Viewed by 633

Abstract

In recent years, super-resolution imaging techniques have been intensely introduced to enhance the azimuth resolution of real aperture scanning radar (RASR). However, there is a paucity of research on the subject of sea surface imaging with small incident angles for complex scenarios. This research endeavors to explore super-resolution imaging for sea surface monitoring, with a specific emphasis on grounded or shipborne platforms. To tackle the inescapable interference of sea clutter, it was segregated from the imaging objects and was modeled alongside I/Q channel noise within the maximum likelihood framework, thus mitigating clutter’s impact. Simultaneously, for characterizing the non-stationary regions of the monitoring scene, we harnessed the Markov random field (MRF) model for its two-dimensional (2D) spatial representational capacity, augmented by a quadratic term to bolster outlier resilience. Subsequently, the maximum a posteriori (MAP) criterion was employed to unite the ML function with the statistical model regarding imaging scene. This hybrid model forms the core of our super-resolution methodology. Finally, a fast iterative threshold shrinkage method was applied to solve this objective function, yielding stable estimates of the monitored scene. Through the validation of simulation and real data experiments, the superiority of the proposed approach in recovering the monitoring scenes and clutter suppression has been verified. Full article

(This article belongs to the Special Issue Recent Advancements in Radar Imaging and Sensing Technology II)

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20 pages, 3313 KiB

Open AccessArticle

Improved Methods for Fourier-Based Microwave Imaging

by Yuri Alvarez López and Fernando Las-Heras Andrés

Sensors 2023, 23(22), 9250; https://doi.org/10.3390/s23229250 - 17 Nov 2023

Viewed by 672

Abstract

Fourier-based imaging has been widely adopted for microwave imaging thanks to its efficiency in terms of computational complexity without compromising image resolution. Together with other backpropagation imaging algorithms like delay-and-sum (DAS), they are based on a far-field approach to the electromagnetic expression relating to fields and sources. To improve the accuracy of these techniques, this contribution presents a modified version of the well-known Fourier-based algorithm by taking into account the field radiated by the Tx/Rx antennas of the microwave imaging system. The impact on the imaged targets is discussed, providing a quantitative and qualitative analysis. The performance of the proposed method for subsampled microwave imaging scenarios is compared against other well-known aliasing mitigation methods. Full article

(This article belongs to the Special Issue Recent Advancements in Radar Imaging and Sensing Technology II)

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Graphical abstract

19 pages, 11004 KiB

Open AccessArticle

System Design and Echo Preprocessing of Spaceborne Squinted Two-Dimensional Beam Scanning Synthetic Aperture Radar

by Wei Xu, Xuhang Lu, Pingping Huang, Weixian Tan, Zhiqi Gao and Yaolong Qi

Sensors 2023, 23(20), 8377; https://doi.org/10.3390/s23208377 - 10 Oct 2023

Viewed by 772

Abstract

Conventional squinted sliding spotlight synthetic aperture radar (SAR) imaging suffers from substantial swath width reduction and complex processing requirements due to the continuous variation in the squint angle and the large range cell migration (RCM) throughout the data acquisition interval. A novel two-dimensional (2D) beam scanning mode for high-resolution wide swath (HRWS) imaging is proposed. The key to the novel imaging mode lies in the synchronous scanning of azimuth and range beams, allowing for a broader and more flexible imaging swath with a high geometric resolution. Azimuth beam scanning from fore to aft was used to improve the azimuth resolution, while range beam scanning was adopted to illuminate the oblique wide swath to avoid the large RCM and the serious swath width reduction. Compared with the conventional sliding spotlight mode, both the swath width and swath length could be extended. According to the echo model of this imaging mode, an echo signal preprocessing approach is proposed. The key points of this approach are range data extension and azimuth data upsampling. A designed system example with a resolution of 0.5 m, swath width of 60 km, and azimuth coverage length of 134 km is presented. Furthermore, a simulation experiment on point targets was carried out. Both the presented system example and imaging results of point targets validated the proposed imaging mode. Full article

(This article belongs to the Special Issue Recent Advancements in Radar Imaging and Sensing Technology II)

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Figure 1

23 pages, 1819 KiB

Open AccessArticle

Drone-Based 3D Synthetic Aperture Radar Imaging with Trajectory Optimization

by Jedrzej Drozdowicz and Piotr Samczynski

Sensors 2022, 22(18), 6990; https://doi.org/10.3390/s22186990 - 15 Sep 2022

Cited by 4 | Viewed by 1661

Abstract

This paper presents a trajectory determination and optimization method of multirotors equipped with a single-channel radar to obtain 3D Synthetic Aperture Radar imaging. The result is a realistic trajectory that allows to obtain an imaging of the assumed quality in less time than using a multi-pass trajectory. The optimization criteria, in addition to the cross-range resolution, are the Peak Sidelobe Ratio (PSLR), Integrated Sidelobe Ratio (ISLR), and time of flight. The algorithm is based on a realistic motion model of the radar platform. This paper presents all the steps of the algorithm and provides simulation results that show its practical applicability. The advantage of the presented approach over the existing ones is indicated and further research directions are proposed. Full article

(This article belongs to the Special Issue Recent Advancements in Radar Imaging and Sensing Technology II)

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15 pages, 4404 KiB

Open AccessArticle

Near-Field High-Resolution SAR Imaging with Sparse Sampling Interval

by Chengyi Zhao, Leijun Xu, Xue Bai and Jianfeng Chen

Sensors 2022, 22(15), 5548; https://doi.org/10.3390/s22155548 - 25 Jul 2022

Viewed by 1340

Abstract

Near-field high-resolution synthetic aperture radar (SAR) imaging is mostly accompanied by a large number of data acquisition processes, which increases the system complexity and device cost. According to extensive reports, reducing the number of sampling points of a radar in space can greatly reduce the amount of data. However, when spatial sparse sampling is carried out, a ghost normally appears in the imaging results due to the high side lobes generated in the azimuth. To address this issue, a technique is introduced in this paper to recover the blank data through amplitude and phase compensation based on the correlation between sparse array sampling through adjacent points. Firstly, the data sampled by the sparse array is compressed in the range direction to obtain the expected data slices in the same range direction. Then, the blank element of the slice is compensated for with amplitude and phase to obtain full aperture data. Finally, the matched filter method is used to aid in the image reconstruction. The simulation results verified that the method proposed in this paper can effectively reconstruct the image under two kinds of sparse sampling conditions. Thus, a simple single-input single-output (SISO) synthetic aperture radar imaging test bench is established. Compared with the results of a 1 mm (1/4

λ

) sampling interval, the quality of the reconstructed image under the condition of a 4 mm (1

λ

) sampling interval still stands using our proposed method. Demonstrated by the experiment, the normalized root-mean-square error(NMSE) is 5.75%. Additionally, when the spatial sampling points are sampled randomly with 30% of the full sampling condition, this method can also restore and reconstruct the image with high quality. Due to the decrease of sampling points, the data volume can be reduced, which is beneficial for improving the scanning speed and alleviating the pressure of data transmission for near-field high resolution SAR imaging systems. Full article

(This article belongs to the Special Issue Recent Advancements in Radar Imaging and Sensing Technology II)

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