A Fast Two Dimensional Joint Super-Resolution B-ISAR Imaging Algorithm Under Low SNR

被引：0
|
作者：
Chen W.-F. [1 ]
Li S.-D. [2 ]
Yang J. [1 ]
Ma X.-Y. [1 ]
机构：
[1] Air Force Early Warning Academy, Wuhan, 430019, Hubei
[2] The Unit 93253 of PLA, Dalian, 116000, Liaoning
来源：
| 2018年 / Chinese Institute of Electronics卷 / 46期
关键词：
2D super-resolution imaging; Bistatic inverse synthetic aperture radar (B-ISAR); Complex approximate message passing; Compressive sensing;
D O I：
10.3969/j.issn.0372-2112.2018.04.011
中图分类号：
学科分类号：
摘要：
In B-ISAR imaging, the range resolution and cross-range resolution are dependent on the signal band and the coherent processing interval, respectively. Generally, the B-ISAR image is seriously affected by noise. In this paper, a matrix form of complex approximate message passing algorithm based on two dimensional coupled dictionaries (MCAMP-TCD) is presented, by considering the 2D coupling sparse feature of the echo. Firstly, the range-azimuth 2D joint B-ISAR imaging model is established. Then the 2D joint super-resolution imaging problem is converted into a complex basis pursuit denoising (C-BPDN) problem through vectorization operation. Secondly, two strategies are implemented to solve C-BPDN problem quickly, the first strategy is utilizing the relation between vectorization operation and Kronecker product to derivate the matrix form of complex approximate message passing algorithm, which can avoid the high computational complexity and memory requirements due to vectorization operation. In second strategy, the two dimensional fast Fourier transform (2D FFT) is introduced to equivalent matrix multiplication, which further reduces the computational complexity of the single iteration. At last, the imaging capability under low signal to noise ratio (SNR) is improved by the ability to accurately approximate the noise threshold of the MCAMP-TCD. Simulation results verify the effectiveness of the proposed method. © 2018, Chinese Institute of Electronics. All right reserved.
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页码：840 / 848
页数：8
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