| Radar Imaging with Quantized Measurements Based on Compressed Sensing | |
Dong, Xiao; Zhang, Yunhua
| |
| Department | 微波遥感部 |
| Source Publication | 2015 Sensor Signal Processing for Defence, SSPD 2015 |
| 2015 | |
| Language | 英语 |
| ISBN | 9781479974443 |
| Abstract | In this paper, we consider the problem of radar imaging with quantized data. The quantized CS (QCS) method is used to reconstruct the radar image of sparse targets from quantized data. The reconstruction problem is derived in the maximum a posteriori (MAP) estimation framework and formulated as a convex optimization problem. We compare the proposed method with the traditional l1-regularization method using 1-D simulated data with different quantization bits. For coarse quantization with 1 or 2 bits, the simulation results show that the QCS method outperforms the l1- regularization method in high SNR situations. For high- resolution quantization with more bits, we derive the conditions under which the l1-regularization method and the QCS method are equivalent. This statement is explained theoretically and confirmed by simulation results. © 2015 IEEE. |
| Conference Name | 5th Sensor Signal Processing for Defence, SSPD 2015 |
| Conference Date | September 9, 2015 - September 10, 2015 |
| Conference Place | Edinburgh, United kingdom |
| Indexed By | EI ; CPCI |
| Document Type | 会议论文 |
| Identifier | http://ir.nssc.ac.cn/handle/122/5371 |
| Collection | 微波遥感部 |
| Recommended Citation GB/T 7714 | Dong, Xiao,Zhang, Yunhua. Radar Imaging with Quantized Measurements Based on Compressed Sensing[C],2015. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| 201507288520.pdf（1084KB） | 会议论文 | 开放获取 | CC BY-NC-SA | Application Full Text | ||
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