Name
Abstract | ||
|---|---|---|
SAR deception jamming method is one of the most important jamming techniques by overlapping a group of fake targets into the SAR images, which can greatly reduce the accuracy of the SAR image interpretation. On the other hands, as a kind of active remote sensing technique, SAR system has less diffuse scattering, and the shadow characteristic is more significant than the optic system. In this paper, the shadow characteristics of the true and false targets are discussed via the simulation experiment, and the convolutional neural network(CNN) is applied for SAR deception jamming target recognition based on the shadow feature. Numerical experiments have shown that the CNN method can effectively distinguish the true and false targets correctly through the shadow feature. |
Year | Venue | Keywords |
|---|---|---|
2017 | European Signal Processing Conference | Deception targets,SAR,CNN,Shadow Feature |
Field | DocType | ISSN |
Shadow,Computer vision,Synthetic aperture radar,Deception,Convolutional neural network,Convolution,Computer science,Artificial intelligence,Jamming,Radar jamming and deception,Diffuse scattering | Conference | 2076-1465 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinxin Tang | 1 | 0 | 1.35 |
| Xiaoling Zhang | 2 | 12 | 4.53 |
| Jun Shi | 3 | 27 | 13.21 |
| Shunjun Wei | 4 | 14 | 8.82 |
| Lei Yu | 5 | 0 | 0.34 |