Project S02 - Digital Compensation in MIMO THz Backscatter Systems
Principal Investigator: Prof. Dr. Aydin Sezgin, RUB ETIT
The design of an energy efficient wireless device that can localize and characterize materials, and is capable of fast acquisition of multiple spots on the target with high spatial resolution, requires the utilization of multiple transmit and receive antennas. In order to obtain a compact design and a small form factor, the transmit and receive antennas are placed close together. In order to characterize various sub-layers of the target, the envisaged system should be capable of resolving backscatters from sub-surfaces of the target. For fast acquisition of the image with reduced complexity, the device should be capable of faithful reconstruction of the scene from a minimal number of samples (sparse sampling). At the same time, for precise characterization, the device should achieve high resolution of material responses.
In realizing these design goals, various challenges have to be addressed. Backscatter and radar systems are inherently limited by transmit signal leaking into the receive chain as a result of imperfect leakage cancellation. This is much more severe in monostatic radar systems, which use the same antenna for transmission and reception. To make matters worse, in MIMO radar, there exists a leakage path between each transmit-receive antenna pair. Practical limitations on sampling rates cause interference between backscatters from sub-layers of the material. Unlike the channel modelling in the ranges of up to a few GHz, each multipath component potentially undergoes different frequency selective fading due to differences in absorption properties of materials at THz frequencies. Classical models based on point target assumption are not directly applicable here, because of the small form factor and short range nature. Additionally, the trade-off between sampling and resolution becomes critical.
In this project, we propose a system of MIMO material characterization in the THz regime that considers the aforementioned challenges and trade-offs. By utilizing tools from signal processing and optimization, this project aims to address these fundamental challenges through the following central objectives:
The project addresses an open research problem, as digital interference compensation, as a complement to its analog counterpart, has not been addressed so far in the research literature for the frequency range considered in MARIE. Thus, the project constitutes an integral part of the MARIE goal to design technologies for optimal characterization and classification of materials.