J4 ›› 2012, Vol. 34 ›› Issue (7): 114-119.
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LIU Jiying,ZHU Jubo
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Abstract:
The classical signal acquisition systems require the sampling rate to be larger than twice the bandwidth of the signal. This makes the very high rate analog to digital conversion become a bottleneck in the design of modern high resolution radar systems. Compressive Sensing theory provides us with a new approach for exact signal acquiring and recovery with low data rate. This paper proposes a new approach for radar sampling and imaging based on compressive sensing. According to the characteristics of the target’s radar scattering, sparse representation of the scattering coefficients is established by using wavelet transform. Moreover, the Fourier ensemble based compressive sampling matrix is designed with the consideration of the SAR imaging principle. Finally, the presented method is validated by numerical simulation, where a better imaging result, especially for the weak target high resolution imaging, is obtained with only 15% data rate compared to the conventional imaging methods. The radar sampling and imaging method presented in this paper can support the development of high resolution radar imaging systems.
Key words: compressive sensing;synthetic aperture radar;sampling;sparse recovery
LIU Jiying,ZHU Jubo. Radar Sampling and Imaging Based on Compressive Sensing Method with Low Data Rate[J]. J4, 2012, 34(7): 114-119.
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http://joces.nudt.edu.cn/EN/Y2012/V34/I7/114