Design of a Microwave Imaging System for Target Identification
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Abstract
The ability to view objects that are otherwise visually inaccessible has been a long sought-after technological function and has a wide variety of potential applications. The research outlined in this thesis details the construction and evaluation of a microwave imaging system to reconstruct images of unknown targets. In our system, we primarily use the common Wi-Fi frequencies of 2.4 GHz and 5 GHz because of the wide availability of commercial microwave components that operate at these frequencies. For the image reconstructions of the targets, we used two separate inverse scattering algorithms. The first algorithm employed is the Linear Sampling Method (LSM) that reconstructed the outer shape of the target, and the second inverse scattering algorithm is a tomography technique that maps the internal material makeup of the target using the Genetic Algorithm (GA) optimization technique. A hardware setup consisting of a circular array of 8 equally spaced antennas was constructed to gather experimental data to test the developed algorithms. In the setup, the 8 antennas were connected to a 2-port Vector Network Analyzer (VNA) using different networks of RF solid-state switches. A fully automatic data acquisition platform was developed by interfacing the VNA and the switches with a personal computer via an Arduino Uno. Our final results show that our experimental system was capable of producing shape reconstructions of metallic targets with simple shapes. Moreover, we quantified the dependence of the accuracy of the reconstruction on the noise level of the measurements and the quality of the components used in the experimental setup.
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Introduction -- Linear sampling method -- Genetic algorithm -- Experimental system -- Conclusion and future work
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M.S.