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Dynamic Waveform Design for Track-Before-Detect Algorithms in Radar

Abstract 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 mean-squared error (MSE). As a result... (more)
Created Date 2011
Contributor Piwowarski, Ryan (Author) / Papandreou-Suppappola, Antonia (Advisor) / Chakrabarti, Chaitali (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering / radar / track before detect / waveform design
Type Masters Thesis
Extent 69 pages
Language English
Reuse Permissions All Rights Reserved
Note M.S. Electrical Engineering 2011
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis