Intelligent Radar Modeling, Imaging and Target Tracking
A Special Issue of Sensors (ISSN 1424-8220) belonging to the section "Radar Sensors".
Deadline for manuscript submissions: 10 May 2027 | Viewed by 70
Editors
Interests: computational electromagnetics methods; antenna array synthesis methods; analysis of electromagnetic scattering characteristics; microwave circuit modeling technology
Special Issues, Collections and Topics in MDPI journals
Interests: antenna array; radar signal processing; SAR processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Background introduction
Radar serves as a crucial active sensor with all-time and all-weather detection capability, supporting extensive applications in airspace surveillance, intelligent transportation, homeland security and earth observation. Stable performance of radar imaging and target tracking is guaranteed by high-accuracy full-chain modeling, including antenna radiation features, electromagnetic wave transmission, target scattering characteristics and echo signal generation. Machine learning greatly facilitates radar research by enabling efficient nonlinear analysis, rapid calculation and strong environmental adaptability. The combination of physical modeling and data-driven algorithms, alongside emerging radar system designs, brings new tools to upgrade radar sensing reliability, flexibility and real-time performance.
This special issue gathers original research and reviews on radar full-chain modeling, intelligent imaging algorithms, target tracking approaches and innovative radar frameworks. As Sensors (ISSN 1424-8220) offers a global academic platform for sensor science, engineering and practical deployment, radar is categorized as a typical electromagnetic active sensor. All contents centered on radar hardware modeling, signal processing and sensing applications fit well within the journal’s scope. This issue complements Sensors’ coverage of advanced sensor technologies and promotes innovation of radar-based sensing devices.
Aim and Scope
This Special Issue aims to collect and disseminate state-of-the-art advances in machine-learning-enabled radar modeling, imaging, and target tracking. It welcomes high-quality original research articles and comprehensive review papers focusing on hybrid physical-data-driven radar modeling theories, intelligent radar system architectures, and machine learning-based sensing algorithms. This issue covers both optimized conventional physical radar methods and innovative machine learning techniques, focusing on effective solutions to balance modeling accuracy, physical interpretability, scenario adaptability, and real-time performance for complex intelligent radar detection applications.
Topics of interest for publication include, but are not limited to:
- Intelligent Radar Antenna Modeling: Digital modeling and performance optimization of antenna arrays, radiation characteristic calibration and error compensation, electromagnetic performance prediction, intelligent beamforming and beam steering optimization, adaptive modeling of smart antennas, and antenna performance evaluation and fault diagnosis.
- Intelligent Radar Channel Propagation Modeling: Electromagnetic propagation modeling for terrestrial, marine and aerial complex scenarios, non-stationary channel feature characterization, multipath propagation and clutter attenuation modeling, and robust adaptive channel modeling for extreme detection environments.
- Intelligent Target Electromagnetic Scattering Modeling: Electromagnetic scattering modeling of complex radar targets, scattering feature extraction for weak, small and stealth targets, target-background scattering coupling modeling, scattering model optimization under small-sample conditions, and multi-band scattering characteristic prediction.
- Intelligent Radar Echo Simulation and Generation: High-precision radar echo simulation, dynamic echo sequence generation for time-varying scenarios, adaptive clutter and noise suppression, scarce echo data augmentation, and virtual-real fusion high-fidelity echo modeling.
- Machine Learning-Based Radar Imaging: Deep learning enhanced high-resolution SAR/ISAR imaging, intelligent reconstruction of sparse radar data, adaptive imaging quality optimization under interference, end-to-end imaging algorithms, lightweight real-time imaging models, and multi-source radar data fusion imaging.
- Intelligent Radar Target Recognition and Tracking: Data-driven target feature classification, adaptive tracking for high-maneuver targets, multi-target association and trajectory optimization, robust tracking under jamming and clutter backgrounds, small-sample and open-set target recognition, large-model radar sensing applications, and multi-sensor fusion tracking technologies.
- Innovative Radar System Mechanisms: Theoretical innovation and system design of next-generation radars, multi-band, multi-polarization and multi-station collaborative radar frameworks, optimized operating mechanisms of SAR, ISAR and new-concept radars, high-efficiency waveform design and signal processing, and advanced radar sensing architectures for complex scenarios.
- Engineering Applications of Intelligent Radar Technology: Practical applications of hybrid radar modeling and intelligent sensing in airspace security, transportation, earth observation and disaster early warning, design of interpretable and lightweight radar algorithms, construction of hybrid physical-data driven sensing frameworks, and system deployment and engineering verification.
Dr. Le Xu
Dr. Rui Li
Dr. Jianqiang Hou
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 250 words) can be sent to the Editorial Office for assessment.
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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 modeling
- machine learning
- intelligent imaging
- target tracking
- electromagnetic scattering
- radar echo simulation
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