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Optical Proximity Correction (OPC) is a part of a family of techniques called Resolution Enhancement Techniques (RET). These techniques are employed to increase the resolution of a lithography system and improve the quality of the printed pattern. The fidelity of the pattern is degraded due to the disparity between the wavelength of light used in optical lithography, and the required size of printed features. In order to improve the aerial image, the mask is modified. This process is called OPC, OPC is an iterative process where a mask shape is modified to decrease the disparity between the required and printed shapes. After each modification the chip is simulated again to quantify the effect of the change in the mask. Thus, lithography simulation is an integral part of OPC and a fast lithography simulator will definitely decrease the time required to perform OPC on an entire chip. A lithography simulator which uses wavelets to compute the aerial image has previously been developed. In this thesis I extensively modify this simulator in order to execute it on a Graphics Processing Unit (GPU). This leads to a lithography simulator that is considerably faster than other lithography simulators and when used in OPC will lead to drastically decreased runtimes. The other work presented in the proposal is a fast OPC tool which allows us to perform OPC on circuits faster than other tools. We further focus our attention on metrics like runtime, edge placement error and shot size and present schemes to improve these metrics.

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Opportunities to use synthetic aperture radar (SAR) in scientific studies and military operations are expanding with the development of small SAR systems that can be operated on small unmanned air vehicles (UAV)s. While the nimble nature of small UAVs make them an attractive platform for many reasons, small UAVs are also more prone to deviate from a linear course due autopilot errors and external forces such as turbulence and wind. Thus, motion compensation and improved processing algorithms are required to properly focus the SAR images. The work of this dissertation overcomes some of the challenges and addresses some of the opportunities of operating SAR on small UAVs. Several contributions to SAR backprojection processing for UAV SARs are developed including: 1. The derivation of a novel SAR backprojection algorithm that accounts for motion during the pulse that is appropriate for narrow or ultra-wide-band SAR. 2. A compensation method for SAR backprojection to enable radiometrically accurate image processing. 3. The design and implementation of a real-time backprojection processor on a commercially available GPU that takes advantage of the GPU texture cache. 4. A new autofocus method that improves the image focus by estimating motion measurement errors in three dimensions, correcting for both amplitude and phase errors caused by inaccurate motion parameters. 5. A generalization of factorized backprojection, which we call the Dually Factorized Backprojection method, that factorizes the correlation integral in both slow-time and fast-time in order to efficiently account for general motion during the transmit of an LFM-CW pulse. Much of this work was conducted in support of the Characterization of Arctic Sea Ice Experiment (CASIE), and the appendices provide substantial contributions for this project as well, including: 1. My work in designing and implementing the digital receiver and controller board for the microASAR which was used for CASIE. 2. A description of how the GPU backprojection was used to improved the CASIE imagery. 3. A description of a sample SAR data set from CASIE provided to the public to promote further SAR research.

Video from aerial surveillance can provide a rich source of data for analysts. From the time-critical perspective of wilderness search and rescue operations, information extracted from aerial videos can mean the difference between a successful search and an unsuccessful search. When using low-cost, payload-limited mini-UAVs, as opposed to more expensive platforms, several challenges arise, including jittery video, narrow fields of view, low resolution, and limited time on screen for key features. These challenges make it difficult for analysts to extract key information in a timely manner. Traditional approaches may address some of these issues, but no existing system effectively addresses all of them in a unified and efficient manner. Building upon a hierarchical dense image correspondence technique, we create a unifying framework for reducing jitter, enhancing resolution, and expanding the field of view while lengthening the time that features remain on screen. It also provides for easy extraction of moving objects in the scene. Our method incorporates locally adaptive warps which allows for robust image alignment even in the presence of parallax and without the aid of internal or external camera parameters. We accelerate the image registration process using commodity Graphics Processing Units (GPUs) to accomplish all of these tasks in near real-time with no external telemetry data.

In this thesis, frame synchronization for iNET formatted SOQPSK-TG communications is considered. Frame synchronization for M-ary linear modulations (MQAM, MPSK, etc.) are known in the literature using pilot detection methods, but are based on a signal model that does not apply to SOQPSK-TG. Maximum likelihood frame synchronizers are derived for an SOQPSK-TG system following assumptions found in the literature. The analysis shows that a reinterpretation of known detectors operating on the samples of the received waveform and locally stored samples of the pilot is the optimum approach for this case. Simulation results for an AWGN channel and several multipath channels verify the performance of the synchronizers.