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Advanced Sensor Technologies for Radar Detection and Imaging Applications
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Advanced Sensor Technologies for Radar Detection and Imaging Applications

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

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 1960

Special Issue Editors

Dr. Tianxian Zhang

E-Mail Website
Guest Editor
School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 610056, China
Interests: radar jamming game evolution technology; detection and communication integrated resource management and control technology; weak target detection technology; multi-functional waveform design
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yong Jia

E-Mail Website
Guest Editor
School of Mechanical and Electrical Engineering, Chengdu University of Technology, Chengdu 610059, China
Interests: radar detection in urban environments; radar based human sensing; emitter recognition
Dr. Xueting Li

E-Mail Website
Guest Editor
School of Aeronautics and Astronautics, Sichuan University, Chengdu 610065, China
Interests: signal detection; multi-sensor resource management; multi-function integrated system resource optimization
Special Issues, Collections and Topics in MDPI journals
Dr. Tuanwei Tian

E-Mail Website
Guest Editor
School of Physics and Electronics, Henan University, Kaifeng 475001, China
Interests: integrated radar and communication; resource optimization; radar task scheduling

Special Issue Information

Dear Colleagues,

Radar can continuously observe the environment at any time and in any weather conditions; therefore, it is an important kind of sensor. Thus, radar has a wide range of applications, such as target detection and imaging. With the advances in both signal processing and hardware design, more flexible radar working modes with better performance have been proposed, together with new theories and methods for advanced radar detection and imaging. Today, radar detection and imaging have become an international hotspot in the field of sensor research.

The present Special Issue aims to exhibit a number of recent advanced techniques in the theory and application of radar detection and imaging. Topics may include, but are not limited to, the following:

  • Radar detection, tracking, parameter estimation;
  • Clutter or jamming suppression;
  • Beamforming;
  • SAR/ISAR/ultra-wideband radar;
  • Radar imaging technology;
  • Synthetic aperture techniques;
  • Signal and data processing;
  • Advanced RF and antenna technologies;
  • Waveform diversity;
  • Radar design and simulation.

Dr. Tianxian Zhang
Prof. Dr. Yong Jia
Dr. Xueting Li
Dr. Tuanwei Tian
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.

Published Papers (2 papers)

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Research

21 pages, 11903 KiB  
Article
A Sub-Aperture Overlapping Imaging Method for Circular Synthetic Aperture Radar Carried by a Small Rotor Unmanned Aerial Vehicle
by Lina Chu, Yanheng Ma, Bingxuan Li, Xiaoze Hou, Yuanping Shi and Wei Li
Sensors 2023, 23(18), 7849; https://doi.org/10.3390/s23187849 - 13 Sep 2023
Viewed by 768
Abstract
Circular synthetic aperture radar (CSAR) can obtain higher image resolution and more target information using 360° observation of the target. Due to the anisotropy of target scattering characteristics in the actual scene, the sub-aperture imaging method is usually used for CSAR imaging. However, [...] Read more.
Circular synthetic aperture radar (CSAR) can obtain higher image resolution and more target information using 360° observation of the target. Due to the anisotropy of target scattering characteristics in the actual scene, the sub-aperture imaging method is usually used for CSAR imaging. However, the uniformly divided overlapping sub-aperture CSAR imaging algorithm only considers phase compensation, ignoring the effect of target scattering characteristics on echo amplitude. In CSAR imaging scenarios carried by small rotor unmanned aerial vehicles (SRUAVs), the size of the observed scene cannot be ignored compared to the distance between the target and the antenna and the effect of the anisotropy of the target scattered energy on the echo amplitude should be considered. In this paper, a sub-aperture CSAR imaging method based on adaptive overlapping sub-aperture is proposed. First, the boundary points of the sub-aperture are determined by analyzing the correlation coefficient and the variation coefficient of the energy function. Next, the overlapping sub-aperture division schemes are automatically generated by screening and combining the boundary points. The sub-aperture images are then generated by a Back Projection (BP) algorithm. Finally, sub-aperture image registration and incoherent superposition are used to generate the final CSAR image. Verified by the CSAR field echo data, the proposed method can realize imaging of the original echo data without the Inertial Navigation System (INS) and Global Positioning System (GPS) observation data. Compared with the CSAR full-aperture BP imaging algorithm, the entropy of the image generated by the proposed method increased by 66.77%. Compared with the sub-aperture CSAR imaging algorithm, the entropy of the image generated by the proposed method was improved by 11.12%, retaining more details of the target, improving the target contour features, and enhancing the focusing effect. Full article
(This article belongs to the Special Issue Advanced Sensor Technologies for Radar Detection and Imaging Applications)
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15 pages, 1170 KiB  
Article
Hierarchical Network-Based Tracklets Data Association for Multiple Extended Target Tracking with Intermittent Measurements
by Kaiyi Jiang, Yiguo Li, Tianli Ma and Lin Li
Sensors 2023, 23(14), 6372; https://doi.org/10.3390/s23146372 - 13 Jul 2023
Viewed by 837
Abstract
The key issue of multiple extended target tracking is to differentiate the origins of the measurements. The association of measurements with the possible origins within the target’s extent is difficult, especially for occlusions or detection blind zones, which cause intermittent measurements. To solve [...] Read more.
The key issue of multiple extended target tracking is to differentiate the origins of the measurements. The association of measurements with the possible origins within the target’s extent is difficult, especially for occlusions or detection blind zones, which cause intermittent measurements. To solve this problem, a hierarchical network-based tracklet data association algorithm (ET-HT) is proposed. At the low association level, a min-cost network flow model based on the divided measurement sets is built to extract the possible tracklets. At the high association level, these tracklets are further associated with the final trajectories. The association is formulated as an integral programming problem for finding the maximum a posterior probability in the network flow model based on the tracklets. Moreover, the state of the extended target is calculated using the in-coordinate interval Kalman smoother. Simulation and experimental results show the superiority of the proposed ET-HT algorithm over JPDA- and RFS-based methods when measurements are intermittently unavailable. Full article
(This article belongs to the Special Issue Advanced Sensor Technologies for Radar Detection and Imaging Applications)
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