AdvisorMarcellin, Michael W.
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractThe radiolocation of arbitrary transmitters is often accomplished by combining pre-detection radio frequency (RF) snapshots and making time-difference-of-arrival (TDOA) and frequency-difference-of-arrival (FDOA) measurements. This requires transporting these snapshots from two or more geographically separated sensors to a common processor where the combined measurements can be made. The available communications bandwidth between these sensor nodes can be a limiting factor in overall system cost and performance. This research presents data compression techniques designed for RF snapshots: lossless methods suitable for any wideband RF sensing application, and lossy methods designed to maximize the quality of TDOA/FDOA measurements and therefore radiolocation accuracy for a given compression ratio. The lossless techniques leverage time and frequency-domain sparseness to transform the snapshots into lower-entropy representations. The lossy techniques leverage the non-uniform contributions of the RF components to TDOA/FDOA measurement quality to emphasize the most important components. In support of this, the general precision of TDOA/FDOA measurements is revisited for low-SNR intercepts. All techniques are demonstrated on actual wideband RF intercepts and simulated examples and their performance is compared to readily available compression tools and relevant published algorithms.
Degree ProgramGraduate College
Electrical & Computer Engineering