NSSC OpenIR  > 微波遥感部
High-Resolution Compressive Sensing Imaging with Stepped-Frequency Noise Signal
Zhang, Yunhua; Dong, Xiao; Gu, Xiang; Zhai, Wenshuai; Zhang, YH (reprint author), Chinese Acad Sci, Ctr Space Sci & Appl Res, Key Lab Microwave Remote Sensing, Beijing 100190, Peoples R China.
Department微波遥感部
Source Publication2012 13TH INTERNATIONAL RADAR SYMPOSIUM (IRS)
2012
Pages170-173
Language英语
ISSN2155-5745
ISBN978-1-4577-1835-9
AbstractHigh-resolution compressive sensing imaging with stepped-frequency noise signal (SFNS) is presented. The SFNS is similar to the stepped - frequency chirp signal (SFCS), which is also composed of a burst of subpulses with their carrier frequencies linearly increased or decreased, but each subpulse is a noise signal instead of a chirp signal. The noise signal of each subpulse is realized by Logistic mapping, i.e. it is a kind of chaotic signal or random like signal. Range compression for SFNS can be as same as that for SFCS when matched filtering (MF) is used. However when the compressive sensing (CS) approach is used, they are quite different. As for SFCS random sampling is performed to echoes of the subchirps while evenly sampling is performed for SFNS. Real data from a moving train is processed to demonstrate the effectiveness of both the signal model and the CS imaging algorithm.; High-resolution compressive sensing imaging with stepped-frequency noise signal (SFNS) is presented. The SFNS is similar to the stepped - frequency chirp signal (SFCS), which is also composed of a burst of subpulses with their carrier frequencies linearly increased or decreased, but each subpulse is a noise signal instead of a chirp signal. The noise signal of each subpulse is realized by Logistic mapping, i.e. it is a kind of chaotic signal or random like signal. Range compression for SFNS can be as same as that for SFCS when matched filtering (MF) is used. However when the compressive sensing (CS) approach is used, they are quite different. As for SFCS random sampling is performed to echoes of the subchirps while evenly sampling is performed for SFNS. Real data from a moving train is processed to demonstrate the effectiveness of both the signal model and the CS imaging algorithm.
KeywordRadar Imaging Noise Signal Logistic Mapping Compresive Sensing
Conference Name13th International Radar Symposium (IRS)
Conference DateMAY 23-25, 2012
Conference PlaceWarsaw, POLAND
Indexed ByEI ; CPCI
Document Type会议论文
Identifierhttp://ir.nssc.ac.cn/handle/122/3395
Collection微波遥感部
Corresponding AuthorZhang, YH (reprint author), Chinese Acad Sci, Ctr Space Sci & Appl Res, Key Lab Microwave Remote Sensing, Beijing 100190, Peoples R China.
Recommended Citation
GB/T 7714
Zhang, Yunhua,Dong, Xiao,Gu, Xiang,et al. High-Resolution Compressive Sensing Imaging with Stepped-Frequency Noise Signal[C]. NEW YORK:IEEE,2012:170-173.
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