A new regularization method for radar cross section imaging
| Autor: | P. Minvielle, Jean-François Giovannelli, Thomas Benoudiba-Campanini, Pierre Massaloux |
|---|---|
| Přispěvatelé: | Centre d'études scientifiques et techniques d'Aquitaine (CESTA), Direction des Applications Militaires (DAM), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Laboratoire de l'intégration, du matériau au système (IMS), Université Sciences et Technologies - Bordeaux 1 (UB)-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Radar cross-section
Mathematical optimization Underdetermined system Computer science 0211 other engineering and technologies 020206 networking & telecommunications 02 engineering and technology Inverse problem Regularization (mathematics) Inverse synthetic aperture radar Radar engineering details Radar imaging 0202 electrical engineering electronic engineering information engineering [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC] Algorithm Image resolution [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing ComputingMilieux_MISCELLANEOUS 021101 geological & geomatics engineering |
| Zdroj: | 2017 11th European Conference on Antennas and Propagation (EUCAP) 2017 11th European Conference on Antennas and Propagation (EUCAP), Mar 2017, Paris, France. ⟨10.23919/EuCAP.2017.7928227⟩ |
| DOI: | 10.23919/EuCAP.2017.7928227⟩ |
| Popis: | Radar Cross Section analysis is the study of the scattering behavior of an object. The objective is to determine the main scatterers from measurements of the backscattered electric field. It is generally achieved by Radar Cross Section imaging. This leads to an ill-posed inverse problem because the system to solve is underdetermined. It is then necessary to regularize the problem by adding prior information. In this paper, a new constrained and sparse regularization method for Radar Cross Section imaging is proposed. It is based on the finite spatial electromagnetic extension of the target and its expected small number of scatterers. A least squares criterion with a L1 penalty and support constraints is developed. It is minimized by an efficient algorithm resting on an Alternating Direction Method of Multipliers. The application to real scattered measurements is very promising, with a limited computation time. Compared to the conventional approach, the image resolution is drastically increased. |
| Databáze: | OpenAIRE |
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