| Random step frequency CSAR imaging based on compressive sensing | |
| Yu, L.; Zhang, Y.; Yu, L. (yljsmile@163.com) | |
| Department | 微波遥感部 |
| Source Publication | Progress In Electromagnetics Research C
 |
| 2012 | |
| Volume | 32Pages:81-94 |
| ISSN | 1937-8718 |
| Language | 英语 |
| Abstract | Circular synthetic aperture radar (CSAR) imaging based on compressive sensing with random step frequency (RSF) as transmitted signal is introduced. CSAR is capable of obtaining both two-dimensional high resolution image and three-dimensional image due to a circular collection trajectory. RSF signal shares good characteristics of noise signals including "thumbtack-shape" ambiguity function, low probability of interception, and strong anti-jamming capability. As a result, CSAR adopting RSF signal can make use of advantages of both CSAR and RSF signal. Compressive sensing is a new data acquisition and reconstruction theorem for sparse or compressible signals, which needs fewer samples to reconstruct signals than traditional Nyquist theorem. Simulation results show that both two-dimensional and three-dimensional targets can be well reconstructed from few samples by applying compressive sensing to RSF CSAR imaging.; Circular synthetic aperture radar (CSAR) imaging based on compressive sensing with random step frequency (RSF) as transmitted signal is introduced. CSAR is capable of obtaining both two-dimensional high resolution image and three-dimensional image due to a circular collection trajectory. RSF signal shares good characteristics of noise signals including "thumbtack-shape" ambiguity function, low probability of interception, and strong anti-jamming capability. As a result, CSAR adopting RSF signal can make use of advantages of both CSAR and RSF signal. Compressive sensing is a new data acquisition and reconstruction theorem for sparse or compressible signals, which needs fewer samples to reconstruct signals than traditional Nyquist theorem. Simulation results show that both two-dimensional and three-dimensional targets can be well reconstructed from few samples by applying compressive sensing to RSF CSAR imaging. |
| Indexed By | EI |
| Funding Project | 中国科学院空间科学与应用研究中心 |
| Document Type | 期刊论文 |
| Identifier | http://ir.nssc.ac.cn/handle/122/3438 |
| Collection | 微波遥感部 |
| Corresponding Author | Yu, L. (yljsmile@163.com) |
| Recommended Citation GB/T 7714 | Yu, L.,Zhang, Y.,Yu, L. . Random step frequency CSAR imaging based on compressive sensing[J]. Progress In Electromagnetics Research C,2012,32:81-94. |
| APA | Yu, L.,Zhang, Y.,&Yu, L. .(2012).Random step frequency CSAR imaging based on compressive sensing.Progress In Electromagnetics Research C,32,81-94. |
| MLA | Yu, L.,et al."Random step frequency CSAR imaging based on compressive sensing".Progress In Electromagnetics Research C 32(2012):81-94. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| 20123281.pdf（378KB） | 开放获取 | CC BY-NC-SA | Application Full Text | |||
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