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| Two Dimensional Joint Super-resolution ISAR Imaging Algorithm Based on Compressive Sensing |
| Wu Min Xing Meng-dao Zhang Lei |
| National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China |
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Abstract For ISAR imaging, the range and cross-range resolutions are constrained by the bandwidth of transmitted signal and Coherent Processing Interval (CPI). In this paper, a novel algorithm of Two-Dimension(2D) joint super-resolution ISAR imaging is addressed based on Compressive Sensing (CS) theory. The ISAR observation signal model is established, where the 2D super-resolution dictionary is formed. By exploiting the sparse prior information of ISAR image, 2D super-resolution imaging is mathematically converted into the l1 norm optimization. The super-resolution ISAR imaging can be realized with accuracy via fast optimization algorithm. In the proposed algorithm, the 2D coupling information of the echo can be effectively utilized through the joint processing of range and azimuth dimension. Besides, the efficiency of the proposed algorithm is improved by using the Conjugate Gradient (CG) algorithm, Fast Fourier Transform (FFT) and Hadamard multiplication operations. Simulation and real-data experiments verify the effectiveness of the proposed algorithm.
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Received: 07 December 2012
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Corresponding Authors:
Wu Min
E-mail: wumin880902@hotmail.com
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2014, Vol. 36 
