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) |
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| 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 |
| Copyright |
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| 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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