Sub-Nyquist SAR via Quadrature Compressive Sampling with Independent Measurements
This paper presents an efficient sampling system for the acquisition of synthetic aperture radar (SAR) data at sub-Nyquist rate. The system adopts a quadrature compressive sampling architecture, which uses modulation, filtering, sampling and digital quadrature demodulation to produce sub-Nyquist or...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-02-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/11/4/472 |
| _version_ | 1828143470387134464 |
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| author | Huizhang Yang Chengzhi Chen Shengyao Chen Feng Xi |
| author_facet | Huizhang Yang Chengzhi Chen Shengyao Chen Feng Xi |
| author_sort | Huizhang Yang |
| collection | DOAJ |
| description | This paper presents an efficient sampling system for the acquisition of synthetic aperture radar (SAR) data at sub-Nyquist rate. The system adopts a quadrature compressive sampling architecture, which uses modulation, filtering, sampling and digital quadrature demodulation to produce sub-Nyquist or compressive measurements. In the sequential transmit-receive procedure of SAR, the analog echoes are modulated by random binary chipping sequences to inject randomness into the measurement projection, and the chipping sequences are independent from one observation to another. As a result, the system generates a sequence of independent structured measurement matrices, and then the resulting sensing matrix has better restricted isometry property, as proved by theoretical analysis. As a standard recovery problem in compressive sensing, image formation from the sub-Nyquist measurements has significantly improved performance, which in turn promotes low sampling/data rate. Moreover, the resulting sensing matrix has structures suitable for fast matrix-vector products, based on which we provide a first-order fast image formation algorithm. The performance of the proposed sampling system is assessed by synthetic and real data sets. Simulation results suggest that the proposed system is a valid candidate for sub-Nyquist SAR. |
| first_indexed | 2024-04-11T19:57:47Z |
| format | Article |
| id | doaj.art-2b0491d9f9d049b69ce587723f76fd5e |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-04-11T19:57:47Z |
| publishDate | 2019-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-2b0491d9f9d049b69ce587723f76fd5e2022-12-22T04:05:50ZengMDPI AGRemote Sensing2072-42922019-02-0111447210.3390/rs11040472rs11040472Sub-Nyquist SAR via Quadrature Compressive Sampling with Independent MeasurementsHuizhang Yang0Chengzhi Chen1Shengyao Chen2Feng Xi3School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, ChinaSchool of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, ChinaSchool of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, ChinaSchool of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, ChinaThis paper presents an efficient sampling system for the acquisition of synthetic aperture radar (SAR) data at sub-Nyquist rate. The system adopts a quadrature compressive sampling architecture, which uses modulation, filtering, sampling and digital quadrature demodulation to produce sub-Nyquist or compressive measurements. In the sequential transmit-receive procedure of SAR, the analog echoes are modulated by random binary chipping sequences to inject randomness into the measurement projection, and the chipping sequences are independent from one observation to another. As a result, the system generates a sequence of independent structured measurement matrices, and then the resulting sensing matrix has better restricted isometry property, as proved by theoretical analysis. As a standard recovery problem in compressive sensing, image formation from the sub-Nyquist measurements has significantly improved performance, which in turn promotes low sampling/data rate. Moreover, the resulting sensing matrix has structures suitable for fast matrix-vector products, based on which we provide a first-order fast image formation algorithm. The performance of the proposed sampling system is assessed by synthetic and real data sets. Simulation results suggest that the proposed system is a valid candidate for sub-Nyquist SAR.https://www.mdpi.com/2072-4292/11/4/472synthetic aperture radarcompressive samplingrestricted isometry propertyfast recovery |
| spellingShingle | Huizhang Yang Chengzhi Chen Shengyao Chen Feng Xi Sub-Nyquist SAR via Quadrature Compressive Sampling with Independent Measurements Remote Sensing synthetic aperture radar compressive sampling restricted isometry property fast recovery |
| title | Sub-Nyquist SAR via Quadrature Compressive Sampling with Independent Measurements |
| title_full | Sub-Nyquist SAR via Quadrature Compressive Sampling with Independent Measurements |
| title_fullStr | Sub-Nyquist SAR via Quadrature Compressive Sampling with Independent Measurements |
| title_full_unstemmed | Sub-Nyquist SAR via Quadrature Compressive Sampling with Independent Measurements |
| title_short | Sub-Nyquist SAR via Quadrature Compressive Sampling with Independent Measurements |
| title_sort | sub nyquist sar via quadrature compressive sampling with independent measurements |
| topic | synthetic aperture radar compressive sampling restricted isometry property fast recovery |
| url | https://www.mdpi.com/2072-4292/11/4/472 |
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