Grant: Canada Research Chairs

Electromagnetic (EM) inversion refers to a set of algorithms and techniques that process a known EM effect in order to infer its unknown cause. The EM inversion framework provides a powerful tool to design EM devices from various forms of user-defined desired specifications, e.g., designing antenna systems to meet desired performance requirements for wireless communications. Similarly, the EM inversion framework enables imaging inaccessible regions from measured EM data, e.g., creating images of the dielectric properties of the human breast for tumor detection. Herein, two overall objectives, under the design and imaging themes, are considered. The first overall objective aims to facilitate and enhance the design of advanced EM metasurfaces. Metasurfaces are thin devices capable of systematically transforming an incoming EM wave to a new desired outgoing one. They can provide various applications in antenna design, analog computing, satellite and wireless communication systems. Advanced metasurfaces offer enhanced functionalities such as reconfigurability and simultaneous spatial and spectral tailoring of EM radiation patterns. However, existing design approaches are not capable of providing a clear and systematic path toward the design of such metasurfaces. In this research, EM inversion approaches will be developed to help design metasurfaces. The main novelty lies in the development of appropriate formulations that link the properties of advanced metasurfaces to various forms of desired specifications. This will shorten the metasurface design cycle by making it more systematic and will provide designers with the ability to precisely balance desired specifications against practical constraints. The second overall objective aims to enhance the image accuracy achievable from EM imaging, which has various applications in biomedical and industrial non-destructive testing applications. In this work, functional metasurface casings as well as matching metasurfaces will be developed for microwave imaging systems. The main novelty of this approach lies in the use of metasurfaces in the imaging hardware, while at the same time including their models into the utilized imaging algorithm. This will enrich the information content of the measured data and reduce the modelling error. This can provide existing microwave imaging applications with a new tool to enhance their images and can also pave the way toward the development of new applications for EM imaging.