Propagation Models and Inversion Approaches for Subsurface and Through-Wall imaging
1Department of ECE (MC 154), University of Illinois at Chicago, Chicago, IL 60607-7053, USA
2Istituto per il Rilevamento Elettromagnetico dell'Ambiente, CNR, 80124 Napoli, Italy
3Department of Electrical and Electronic Engineering, The Hong Kong University, Pokfulam, Hong Kong; University of Illinois at Urbana-Champaign, Champaign, IL 61820-5711, USA
Propagation Models and Inversion Approaches for Subsurface and Through-Wall imaging
Description
The capability of imaging underground and through buildings is paramount for rescue operations, such as in an earthquake, as well as for monitoring in security or defense applications. Electromagnetic waves play a primary role in probing these scenarios due to their capability to penetrate various media. Moreover, systems based on electromagnetic waves, such as ground penetrating radars, can be easily deployed, which is important for rescue operations. Imaging in these scenarios is challenging because of the pertinent inverse problem. It is further complicated by many other factors, such as the presence of unknown different materials and unknown obstacle geometries. Solutions have been obtained, in many cases using simplified scattering models, to reduce the complexity of the problem by linearizing it. Existing imaging systems are based on single antenna or multiple antennas. The antennas could be either fixed or moving. In this special issue, we are seeking novel contributions to propagation models and inversion approaches for subsurface and through-wall imaging. Examples of topics of interest include, but are not limited to:
- Forward modeling of the electromagnetic scattering and propagation: ability to tackle the complexity of the scenarios in realistic conditions by accounting for factors including antenna modeling, computational complexity, and medium characterization
- Inversion methods for high-resolution and effective imaging of hidden and buried targets in 3D scenes
- Inversion approaches for “quantitative” reconstruction in controlled and realistic conditions
- Development and analysis of new methods for multiple-antenna systems data processing new algorithms to inverse image large problems
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