Calibration, Characterization and Optimization of Microwave Imaging System for Grain Monitoring

Microwave Imaging (MWI) is an emerging modality where the goal is to estimate the electrical properties of an object-of-interest. This is done by transmitting a microwave signal into the OI and collecting measurements outside the OI. The measurements are inputs to an optimization algorithm that solves for the unknown electrical properties. It has been proven using computational techniques that the proposed modality can be successfully adapted for monitoring moisture content inside grain bins. Based on the aforementioned study, prototype hardware and instruments, used in the actual grain-bin MWI system, have been designed and built. In this work, calibration techniques for actual datasets collected from a grain-bin MWI system are investigated and applied. The calibrated data are then inverted using state-of-the-art inversion algorithms. Further, novel techniques for reducing the modelling error via hardware optimization are studied and tested using scaled prototype metallic chambers. The research is conducted at the Electromagnetic Imaging Laboratory at the University of Manitoba.

Faculty Supervisor:

Dr. Joe LoVetri

Student:

Amer Zakaria

Partner:

TRTech

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

University of Manitoba