Name
Abstract | ||
|---|---|---|
Range ambiguity in synthetic aperture radar (SAR) imaging primarily arises from scattered energy of bright targets outside the interested region. So to reduce the ambiguity, we need to identify these targets additionally, which yields an ill-posed problem. To find a feasible solution where the range ambiguity can be sufficiently reduced, we propose in this paper a new method using compressed sensing, a theory which tells when sparse signal can be reconstruct from undetermined linear system, by observing that the recognizable targets are approximately sparse in the ambiguous range zones. Therefore, it is possible to reconstruct the main region and identify the ambiguous targets simultaneously. The simulation results demonstrate the validation of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/IGARSS.2012.6350582 | IGARSS |
Keywords | Field | DocType |
lq regularization,synthetic aperture radar,sparse signal,range ambiguity suppression,energy scattering,synthetic aperture radar imaging,sparse regularization,image reconstruction,compressed sensing,sar range ambiguity suppression,radar imaging,azimuth,linear systems | Iterative reconstruction,Continuous-wave radar,Computer vision,Radar imaging,Side looking airborne radar,Synthetic aperture radar,Computer science,Remote sensing,Inverse synthetic aperture radar,Artificial intelligence,Ambiguity,Compressed sensing | Conference |
Volume | Issue | ISSN |
null | null | 2153-6996 E-ISBN : 978-1-4673-1158-8 |
ISBN | Citations | PageRank |
978-1-4673-1158-8 | 1 | 0.40 |
References | Authors | |
4 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jian Fang | 1 | 1 | 0.40 |
| Zongben Xu | 2 | 3203 | 198.88 |
| chenglong jiang | 3 | 22 | 3.98 |
| bingchen zhang | 4 | 110 | 17.19 |
| Wen Hong | 5 | 355 | 49.85 |