Support Detection for SAR Tomographic Reconstructions from Compressive Measurements
The problem of detecting and locating multiple scatterers in multibaseline Synthetic Aperture Radar (SAR) tomography, starting from compressive measurements and applying support detection techniques, is addressed. Different approaches based on the detection of the support set of the unknown sparse v...
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2015/949807 |
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| _version_ | 1832551868501327872 |
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| author | Alessandra Budillon Gilda Schirinzi |
| author_facet | Alessandra Budillon Gilda Schirinzi |
| author_sort | Alessandra Budillon |
| collection | DOAJ |
| description | The problem of detecting and locating multiple scatterers in multibaseline Synthetic Aperture Radar (SAR) tomography, starting from compressive measurements and applying support detection techniques, is addressed. Different approaches based on the detection of the support set of the unknown sparse vector, that is, of the position of the nonzero elements in the unknown sparse vector, are analyzed. Support detection techniques have already proved to allow a reduction in the number of measurements required for obtaining a reliable solution. In this paper, a support detection method, based on a Generalized Likelihood Ratio Test (Sup-GLRT), is proposed and compared with the SequOMP method, in terms of probability of detection achievable with a given probability of false alarm and for different numbers of measurements. |
| format | Article |
| id | doaj-art-2de3fc3367e547ecb7c3964fbc97f288 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-2de3fc3367e547ecb7c3964fbc97f2882025-02-03T06:00:09ZengWileyThe Scientific World Journal2356-61401537-744X2015-01-01201510.1155/2015/949807949807Support Detection for SAR Tomographic Reconstructions from Compressive MeasurementsAlessandra Budillon0Gilda Schirinzi1Dipartimento di Ingegneria, Università degli Studi di Napoli “Parthenope”, Centro Direzionale di Napoli, Isola C4, 80143 Napoli, ItalyDipartimento di Ingegneria, Università degli Studi di Napoli “Parthenope”, Centro Direzionale di Napoli, Isola C4, 80143 Napoli, ItalyThe problem of detecting and locating multiple scatterers in multibaseline Synthetic Aperture Radar (SAR) tomography, starting from compressive measurements and applying support detection techniques, is addressed. Different approaches based on the detection of the support set of the unknown sparse vector, that is, of the position of the nonzero elements in the unknown sparse vector, are analyzed. Support detection techniques have already proved to allow a reduction in the number of measurements required for obtaining a reliable solution. In this paper, a support detection method, based on a Generalized Likelihood Ratio Test (Sup-GLRT), is proposed and compared with the SequOMP method, in terms of probability of detection achievable with a given probability of false alarm and for different numbers of measurements.http://dx.doi.org/10.1155/2015/949807 |
| spellingShingle | Alessandra Budillon Gilda Schirinzi Support Detection for SAR Tomographic Reconstructions from Compressive Measurements The Scientific World Journal |
| title | Support Detection for SAR Tomographic Reconstructions from Compressive Measurements |
| title_full | Support Detection for SAR Tomographic Reconstructions from Compressive Measurements |
| title_fullStr | Support Detection for SAR Tomographic Reconstructions from Compressive Measurements |
| title_full_unstemmed | Support Detection for SAR Tomographic Reconstructions from Compressive Measurements |
| title_short | Support Detection for SAR Tomographic Reconstructions from Compressive Measurements |
| title_sort | support detection for sar tomographic reconstructions from compressive measurements |
| url | http://dx.doi.org/10.1155/2015/949807 |
| work_keys_str_mv | AT alessandrabudillon supportdetectionforsartomographicreconstructionsfromcompressivemeasurements AT gildaschirinzi supportdetectionforsartomographicreconstructionsfromcompressivemeasurements |