Browsing by Author "Eustice, Dylan Scott, 1992-"
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Item Adaptive radar waveform synthesis via alternating projections.(2015-12-02) Eustice, Dylan Scott, 1992-; Baylis, Charles Passant, 1979-As the number of wireless broadband devices occupying our airwaves grows at a rapid rate, the resultant decrease in available spectrum for current technologies and increasingly stringent regulations on band compliance has necessitated adaptive RF technologies which can respond to the spectrum crisis. The task of maintaining the effectiveness of our RF technology with a shrinking spectrum has generated work in a number of fields, notably cognitive radar. This work focuses on developing an algorithm which can adaptively produce waveforms with desired accuracy in the range-Doppler domain, measured by the ambiguity function, for radar detection while also having characteristics which allow for efficient amplifier operation and spectral compliance.Item A Model for SIFT Optimization Using FPAA-Driven Block Convolution(2014-06-02) Eustice, Dylan Scott, 1992-; Koziol, Scott M.; Electrical and Computer Engineering.; Baylor University.; Honors College.The Scale Invariant Feature Transform (SIFT) is a useful algorithm for describing local features in an image. This research successfully demonstrates a model for optimizing SIFT using a Field Programmable Analog Array (FPAA). A method is presented which theoretically can reduce SIFT run time by nearly 50% by greatly limiting the image area required to search for SIFT features. Block convolution is a simplified, non-overlapping method of convolution which is computed with the FPAA. The block convolution between the input image and a specially designed kernel is used to determine potential regions of interest. The performance of several different types of kernels will be compared, most of which were produced using an evolutionary search algorithm. A threshold is then applied to the filtered image produced by the FPAA and regions which are unlikely to produce matches are masked. By removing the necessity to search in areas of the image where a match is unlikely to be found, we see a more efficient implementation of SIFT that also demonstrates the usefulness of new FPAA technology.