TY - GEN
T1 - Parallel frequency radar via compressive sensing
AU - You, Yanan
AU - Li, Chunsheng
AU - Yu, Ze
PY - 2011
Y1 - 2011
N2 - Traditional radar utilizes Shannon-Nyquist theorem for high bandwidth signal sampling, which induces the complicated system. Compressive sensing (CS) indicates that the compressible signal using a few measurements can be reconstructed by solving a convex optimization problem. Thus, the huge amount of data according to high Shannon-Nyquist rate is significantly reduced by compressive sensing. Parallel frequency radar theoretically cannot degrade the resolution compared with a traditional radar system and effectively reduces the sampling rate. In this paper, we focus on the data processing of the novel radar system. Basing on a sufficient structure, an algorithm of target scene reconstruction in pursuance of compressive sensing applied to the novel radar is proposed. Several simulations demonstrate the feasibility and the superiority of parallel frequency radar via compressive sensing.
AB - Traditional radar utilizes Shannon-Nyquist theorem for high bandwidth signal sampling, which induces the complicated system. Compressive sensing (CS) indicates that the compressible signal using a few measurements can be reconstructed by solving a convex optimization problem. Thus, the huge amount of data according to high Shannon-Nyquist rate is significantly reduced by compressive sensing. Parallel frequency radar theoretically cannot degrade the resolution compared with a traditional radar system and effectively reduces the sampling rate. In this paper, we focus on the data processing of the novel radar system. Basing on a sufficient structure, an algorithm of target scene reconstruction in pursuance of compressive sensing applied to the novel radar is proposed. Several simulations demonstrate the feasibility and the superiority of parallel frequency radar via compressive sensing.
KW - Compressive sensing
KW - parallel frequency radar
KW - radar signal processing
KW - simulations
UR - https://www.scopus.com/pages/publications/80955139599
U2 - 10.1109/IGARSS.2011.6049759
DO - 10.1109/IGARSS.2011.6049759
M3 - 会议稿件
AN - SCOPUS:80955139599
SN - 9781457710056
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 2696
EP - 2699
BT - 2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011 - Proceedings
T2 - 2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011
Y2 - 24 July 2011 through 29 July 2011
ER -