High-speed Target ISAR Imaging via Compressed Sensing Based on Sparsity in Fractional Fourier Domain

Compressed sensing （CS） provides great potential to reduce radar sampling rate while improve the imaging performance. In this paper, the application of CS to ISAR imaging of hlgh-speed space targets is introduced. Firstly, based on the analysis of the echo model of highspeed targets, we elucidate th...

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Bibliographic Details
Published in:电子学报：英文版 2013-07, Vol.22 (3), p.648-654
Main Author: LIU Jihong LI Xiang GAO Xunzhang ZHUANG Zhaowen
Format: Article
Language:English
Subjects:
ISAR成像
优化搜索算法
传感
分数傅里叶变换
压缩
目标回波
稀疏
非线性最优化
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Summary:Compressed sensing （CS） provides great potential to reduce radar sampling rate while improve the imaging performance. In this paper, the application of CS to ISAR imaging of hlgh-speed space targets is introduced. Firstly, based on the analysis of the echo model of highspeed targets, we elucidate that the dechirped high-speed target echo is of sparsity in fractional Fourier domain. Then the Analog-to-information conversion （AIC） is used to take compressive measurements, following which the radar image can be recovered via nonlinear optimization. In particular, considering the non-cooperative characteristic of targets, an optimization search algorithm based on sparsity of the reconstructed range profiles is presented, so as to find the optimal transform order of fractional Fourier transform. Experiment results from both simulated data and measured data show the validity and superiority of the proposed imaging method.
ISSN:1022-4653