Improving Radar Imaging with Computational Imaging and Novel Antenna Design

dc.contributor.advisor

Marks, Daniel L

dc.contributor.advisor

Brady, David J

dc.contributor.author

Zhu, Ruoyu

dc.date.accessioned

2018-03-20T17:53:08Z

dc.date.available

2018-08-29T08:17:11Z

dc.date.issued

2017

dc.department

Electrical and Computer Engineering

dc.description.abstract

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.

dc.identifier.uri

https://hdl.handle.net/10161/16229

dc.subject

Electrical engineering

dc.subject

Remote sensing

dc.subject

Physics

dc.subject

3D printing antennas

dc.subject

adaptive imaging

dc.subject

compressed sensing

dc.subject

computational imaging

dc.subject

frequency diverse antenna

dc.subject

millimeter wave imaging

dc.title

Improving Radar Imaging with Computational Imaging and Novel Antenna Design

dc.type

Dissertation

duke.embargo.months

5

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