Title:
MAC layer assisted localization in wireless environments with multiple sensors and multiple emitters

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Author(s)
Garver, Paul W.
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Advisor(s)
Coyle, Edward J.
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Supplementary to
Abstract
Extreme emitter density (EED) RF environments, defined as 10k-100k emitters within a footprint of less than 1 km squared, are becoming increasingly common with the proliferation of personal devices containing myriad communication standards (e.g. WLAN, Bluetooth, 4G, etc). Attendees at concerts, sporting events, and other such large-scale events desire to be connected at all times, creating tremendous spectrum management challenges, especially in unlicensed frequencies such as 2.4 GHz, 5 GHz, or 900 MHz Industrial, Scientific, and Medical (ISM) bands. In licensed bands, there are often critical communication systems such as two-way radios for emergency personnel which must be free from interference. Identification and localization of a non-conforming or interfering Emitter of Interest (EoI) is important for these critical systems. In this dissertation, research is conducted to improve localization for these EED RF environments by exploiting side information available at the Medium Access Control (MAC) layer. The primary contributions of this research are: (1) A testbed in Bobby Dodd football stadium consisting of three spatially distributed, time-synchronized RF Sensor Nodes (RFSN) collecting and archiving complex baseband samples for algorithm development and validation. (2) A modeling framework and analytical results on the benefits of exploiting the structure of the MAC layer for associating physical layer measurements, such as Time Difference of Arrivals (TDoA), to emitters. (3) A three stage localization algorithm exploiting time between packets and a constrained geometry to shrink the error ellipse of the emitter position estimate. The results are expected to improve localization accuracy in wireless environments when multiple sensors observe multiple emitters using a known communications protocol within a constrained geometry.
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Date Issued
2017-10-12
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Dissertation
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