Improving Radar Imaging with Computational Imaging and Novel Antenna Design
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Traditional radar imaging systems are implemented using the focal plane
technique, steering beam antennas, or synthetic aperture imaging. These conventional
methods require either a large number of sensors to form a focal plane array similar to the
idea of an optical camera, or a single transceiver mechanically scanning the field of view.
The former results in expensive systems whereas the latter results in long acquisition time.
Computational imaging methods are widely used for the ability to acquire information
beyond the recorded pixels, thus are ideal options for reducing the number of radar
sensors in radar imaging systems. Novel antenna designs such as the frequency diverse
antennas are capable of optimizing antennas for computational imaging algorithms. This
thesis tries to find a solution for improving the efficiency of radar imaging using a method
that combines computational imaging and novel antenna designs. This thesis first
proposes two solutions to improve the two aspects of the tradeoff respectively, i.e. the
number of sensors and mechanical scanning. A method using time-of-flight imaging
algorithm with a sparse array of antennas is proposed as a solution to reduce the number
of sensors required to estimate a reflective surface. An adaptive algorithm based on the
Bayesian compressive sensing framework is proposed as a solution to minimize
mechanical scanning for synthetic aperture imaging systems. The thesis then explores the
feasibility to further improve radar imaging systems by combining computational
imaging and antenna design methods as a solution. A rapid prototyping method for
manufacturing custom-designed antennas is developed for implementing antenna
designs quickly in a laboratory environment. This method has facilitated the design of a
frequency diverse antenna based on a leaky waveguide design, which can be used under
computational imaging framework to perform 3D imaging. The proposed system is
capable of performing imaging and target localization using only one antenna and
without mechanical scanning, thus is a promising solution to ultimately improve the
efficiency for radar imaging.
Zhu, Ruoyu (2017). Improving Radar Imaging with Computational Imaging and Novel Antenna Design. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/16229.
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