This thesis addresses the use of an electronic reconfigurable surface (ERS) attached to an axisymmetric paraboloidal reflector antenna to mitigate interference through nulling for radio astronomy applications. The ERS is a reflectarray that consists of multiple elements, which can be electronically controlled to modify the reflected field. Previous research focused on a "conformal" system with elements placed on a parabololoidal surface extending beyond the unmodified reflector. These studies concluded that nulling could be achieved without compromising the gain and shape of the main lobe. This thesis builds on previous research by addressing two topics. The first topic is minimization of the ERS rim width. A closed form expression for the minimum width required for effective nulling in the close-in sidelobes is derived in this thesis. The second topic addressed in this thesis is ERS configurations comprised of flat panels as an alternative to the conformal ERS implementation. Flat panels may be easier to manufacture compared to their conformal counterpart. Flat panel ERS implementations are evaluated, and it is concluded that they are a suitable alternative to conformal ERS implementation. / Master of Science / This thesis utilizes the state-of-the art electronic reconfigurable surface (ERS) attached to a reflector antenna to mitigate interference for radio astronomy applications. The ERS is an array that can be controlled electronically to modify the radiation from the reflector. Previous research focused on configuring the ERS attached conformally to the reflector to null interference in a direction. This thesis appends previous research by addressing two topics. The first topic is the minimization of the ERS width for the conformal implementation. A closed form expression for the minimum ERS width is derived in this thesis. The second topic is to explore an ERS topology that consists of flat panels attached to the reflector. This topology is explored since flat ERS panels may be easier to manufacture. It is concluded that the flat panel ERS implementation is a suitable alternative to the conformal ERS implementation for interference mitigation.

No description available.

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 108-116). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 103-111). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 130-139). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 91-96). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--University of Texas at Austin, 2002. / Vita. Includes bibliographical references. Available also from UMI Company.

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references (leaves 116-118). Also available in electronic version. Access restricted to campus users.

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

This work explored the design considerations on the real-time medical ultrasound adaptive beamformer implementations using different computing platforms: CPU, GPU and FPGA. Adaptive beamforming has been well considered as an advanced solution for improving the image quality of medical ultrasound imaging machines. Although it provides promising improvements in lateral resolution, image contrast and imaging penetration depth, the use of adaptive beamforming is substantially more computationally demanding than conventional delay-and-sum beamformers. In order not to compromise the real-time performance of medical ultrasound systems, an accelerated solution is desirable. In this work, CPU implementation was used as a baseline implementation, based on which the intrinsic characteristics of the algorithm were analyzed. After the analysis of a particular adaptive beamforming algorithm, minimum-variance adaptive beamforming, two design parameters M and L were found to affect the implementation performance in two aspects: computational demand and image quality. The trends of the two aspects were contradictory with respect to the increment of M and L values. In our experiments, when M and L increased, the computational demand increased in a cubic curve; meanwhile, the image quality did not have much improvement when the increased values of M and L entered certain ranges. Since we targeted at a real-time solution without sacrificing the good image quality that adaptive beamforming proposed, a tradeoff was made on the selection of M and L values to balance the two contradictory requirements. Built upon the theoretical algorithmic analysis of the real-time adaptive beamformer realization, the implementations were developed with FPGA and GPU. While a dedicated hardware solution might be able to address the computational demand of the particular design, the need for an efficient algorithm exploration framework demanded a reprogrammable platform solution that was high-performance and easily reconfigurable. Besides, although a simple processor could provide convenient algorithm exploration via software development environment, real-time performance was usually not achievable. As a result, a reprogrammable medical ultrasound research platform for investigating advanced imaging algorithms was constructed in our project. The use of FPGA and GPU for implementing the real-time adaptive beamformer on our platform was explored. In our test cases, both FPGA- and GPUbased solutions achieved real-time throughput exceeding 80 frames-per-second, and over 38x improvement when compared to our baseline CPU implementation. Moreover, the implementations were also evaluated in terms of portability, data accuracy, programmability, and system integration. Due to its high power consumption, high-performance GPU solution is best suited for bedside applications, while FPGAs are more suitable for portable and hand-held medical ultrasound machines. Besides, while the development time on GPU platform remains much lower than its FPGA counterpart, the FPGA solution is effective in providing the necessary I/O bandwidth to enable an end-to-end real-time reconfigurable medical ultrasound image formation system. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy