Modern Advances in Electromagnetic Imaging and Remote Sensing: Enabling Hardware, Computational Techniques and Machine Learning

Dear Colleagues,

The field of radar imaging and remote sensing has been at the forefront of applied electromagnetics for several decades. Because inverse problems are computationally demanding and require the collection of signals imposing the use of complex RF architectures, the search for alternative techniques to simplify the hardware requirements and signal processing has been a major thrust within the remote sensing and radar imaging community. This goal has gained a dramatic traction following the recent evolution of computational techniques, such as compressive sensing, and recent progress in the machine learning field.

Due to the recent advancements in enabling component technology, particularly within the millimeter-wave and submillimeter-wave frequency regimes, and signal processing algorithms, there has been a growing interest in developing innovative sensor technologies with the goals of maximizing the information content in retrieved images using techniques such as polarimetry, minimizing the computational complexity of image reconstruction process, lowering power consumption, and reducing physical hardware footprint.

The objective of this Special Issue is to bring together the electromagnetic sensing and radar imaging communities to present the state-of-the-art research conducted in this field and highlight the emerging technologies in hardware, computational techniques and machine learning for microwave, mmW, and THz radar imaging and remote sensing technology.  

The scope of this Special Issue includes (but not limited to):

• Reconstruction and signal processing algorithms, including but not limited to Fourier-domain reconstruction techniques in radar and remote sensing, such as range-migration, and real-time reconstruction using parallel-computing and computational imaging;
• Machine learning as applied to remote sensing and imaging applications at microwave, millimeter-wave, and submillimeter-wave frequencies;
• Active and passive enabling hardware architectures, including new antenna topologies, synthesizers, and signal processing units. Design, synthesis, and analysis of new antenna architectures for sensing and imaging relying on emerging techniques, including but not limited to metamaterials, multiple-input–multiple-output (MIMO) antennas, electronically scanned antennas, on-chip antennas, and 3D printed antennas;
• Imaging hardware and software: Enabling technologies for, among others, sensor fusion (acoustics, microwave, mmW, THz, optics), innovative RF backend and signal processing units, and imaging leveraging modern advances in FPGAs and GPUs.

Dr. Okan Yurduseven
Dr. Thomas Fromenteze
Dr. Jaime Laviada
Dr. Yanghyo Rod Kim
Guest Editors

Manuscript Submission Information

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