Off-campus UMass Amherst users: To download campus access theses, please use the following link to log into our proxy server with your UMass Amherst user name and password.
Non-UMass Amherst users: Please talk to your librarian about requesting this thesis through interlibrary loan.
Theses that have an embargo placed on them will not be available to anyone until the embargo expires.
Electrical & Computer Engineering
Master of Science in Electrical and Computer Engineering (M.S.E.C.E.)
Year Degree Awarded
Month Degree Awarded
waveform design, radar target classification, digital-to-analog converter, linearization, predistortion, precompensation
This thesis work consists of two research projects. The first project presented is on waveform design for car radars. These radars are used to detect other vehicles to avoid collision. In this project, we attempt to find the best waveform that distinguishes large objects from small ones. This helps the radar system reach more reliable decisions. We consider several models of the problem with varying complexity. For each model, we present optimization results calculated under various constraints regarding how the waveform is generated and how the reflected signal is processed. The results show that changing the radar waveform can result in better target classification.
The second project is about digital-to-analog converter (DAC) linearization. Ideally, DACs have a linear input-output relation. In practice, however, this relation is nonlinear which may be harmful for many applications. A more linear input-output relation can be achieved by modifying the input to a DAC. This method, called predistortion, requires a good understanding of how DAC errors contribute to the nonlinearity. Assuming a simple DAC model, we investigate how different error functions lead to different types of nonlinearities through theoretical analyses and supporting computer simulations. We present our results in terms of frequency spectrum calculations. We show that the nonlinearity observed at the output strongly depends on how the error is modeled. These results are helpful in designing a predistorter for linearization.
Dennis L. Goeckel