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Integrated Waveform-Agile Multi-Modal Track-before-Detect Algorithms for Tracking Low Observable Targets

Abstract In this thesis, an integrated waveform-agile multi-modal tracking-beforedetect sensing system is investigated and the performance is evaluated using an experimental platform. The sensing system of adapting asymmetric multi-modal sensing operation platforms using radio frequency (RF) radar and electro-optical (EO) sensors allows for integration of complementary information from different sensors. However, there are many challenges to overcome, including tracking low signal-to-noise ratio (SNR) targets, waveform configurations that can optimize tracking performance and statistically dependent measurements. Address some of these challenges, a particle filter (PF) based recursive waveformagile track-before-detect (TBD) algorithm is developed to... (more)
Created Date 2012
Contributor Liu, Shubo (Author) / Papandreou-Suppappola, Antonia (Advisor) / Duman, Tolga (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering / Embedded exponential families / Particle Filter / Track-before-detect / Waveform-agile
Type Masters Thesis
Extent 75 pages
Language English
Reuse Permissions All Rights Reserved
Note M.S. Electrical Engineering 2012
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis