Object detection and image reconstruction using microwave technology

Abstract

Microwave imaging holds significant potential in the medical field, offering advantages over traditional methods like X-rays and MRI. It is both cost-effective and uses non-ionizing radiation, making it a safer option. Although microwave tomography is complex, it shows promise for imaging soft tissues. The longer wavelengths used are more affected by diffraction, meaning that the assumption of straight-line propagation in a dielectric medium is generally valid only at higher frequencies, such as in the ultraviolet or gamma ray range. Using a circular radar aperture for imaging, combined with advanced post-processing reconstruction techniques, can enhance the overall performance of the imaging system. Simulations demonstrate that employing an ultrawide band (UWB) increases depth resolution, while improved angular resolution enhances cross-range accuracy, making it possible to pinpoint the location and range of targets. However, there's a tradeoff between attenuation and resolution that varies with frequency, especially in materials that absorb energy. A stable imaging system is essential for consistent measurements, particularly when removing artifacts. My attempt at reconstructing an image from measured data was semi-successful due to a high margin of phase error, which led to inconsistencies in the results. Future research has substantial potential to improve image reconstruction quality further. MATLAB’s extensive library resources make it a valuable tool for advancing these enhancements.