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ASU Electronic Theses and Dissertations

This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at

As the demand for wireless systems increases exponentially, it has become necessary for different wireless modalities, like radar and communication systems, to share the available bandwidth. One approach to realize coexistence successfully is for each system to adopt a transmit waveform with a unique nonlinear time-varying phase function. At the receiver of the system of interest, the waveform received for process- ing may still suffer from low signal-to-interference-plus-noise ratio (SINR) due to the presence of the waveforms that are matched to the other coexisting systems. This thesis uses a time-frequency based approach to increase the SINR of a system by …

Gattani, Vineet Sunil, Papandreou-Suppappola, Antonia, Richmond, Christ, et al.
Created Date

In this thesis, an adaptive waveform selection technique for dynamic target tracking under low signal-to-noise ratio (SNR) conditions is investigated. The approach is integrated with a track-before-detect (TBD) algorithm and uses delay-Doppler matched filter (MF) outputs as raw measurements without setting any threshold for extracting delay-Doppler estimates. The particle filter (PF) Bayesian sequential estimation approach is used with the TBD algorithm (PF-TBD) to estimate the dynamic target state. A waveform-agile TBD technique is proposed that integrates the PF-TBD with a waveform selection technique. The new approach predicts the waveform to transmit at the next time step by minimizing the predicted …

Piwowarski, Ryan, Papandreou-Suppappola, Antonia, Chakrabarti, Chaitali, et al.
Created Date