An l1-regularized least squares algorithm for reconstructing step-frequency ground penetrating radar images
| Autor: | John M. M. Anderson, Mandoye Ndoye, Henry C. Ogworonjo, Lam H. Nguyen |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
business.industry Pulse-Doppler radar 020206 networking & telecommunications 02 engineering and technology Impulse (physics) Radar lock-on Physics::Geophysics Continuous-wave radar Bistatic radar Radar engineering details Radar imaging Ground-penetrating radar 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Algorithm Low probability of intercept radar |
| Zdroj: | 2016 IEEE Radar Conference (RadarConf). |
| DOI: | 10.1109/radar.2016.7485297 |
| Popis: | Impulse-based ground penetrating radar (GPR) has been proposed as a way to detect landmines and improvised explosive devices (IEDs). However, a drawback of such radar systems is the difficulty in transmitting a signal with an arbitrary bandwidth and shape. Step-frequency GPR has been recognized as a way to precisely control the bandwidth and spectral shape of the transmitted pulse. In this paper, we extend a previously developed-regularized least squares algorithm, which has been successfully applied to impulse-based GPR image reconstruction, to step-frequency GPR. We investigate the performance of the proposed algorithm using simulated step-frequency GPR data. The initial results are promising. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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