JOURNAL OF RADARS
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JOURNAL OF RADARS  2016, Vol. 5 Issue (1): 82-89    DOI: 10.12000/JR16012
Sparse Microwave Imaging Technology Current Issue | Next Issue | Archive | Adv Search |
Space Group Debris Imaging Based on Sparse Sample
Zhu Jiang*① Deng Jiaxin Liao Guisheng Zhu Shengqi
(National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China)
(China Flight Test Establishment, Xi'an 710089, China)
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Abstract 

Space group debris imaging is difficult with sparse data in low Pulse Repetition Frequency (PRF) spaceborne radar. To solve this problem in the narrow band system, we propose a method for space group debris imaging based on sparse samples. Due to the diversity of mass, density, and other factors, space group debris typically rotates at a high speed in different ways. We can obtain angular velocity through the autocorrelation function based on the diversity in the angular velocity. The scattering field usually presents strong sparsity, so we can utilize the corresponding measurement matrix to extract the data of different debris and then combine it using the sparse method to reconstruct the image. Furthermore, we can solve the Doppler ambiguity with the measurement matrix in low PRF systems and suppress some energy of other debris. Theoretical analysis confirms the validity of this methodology. Our simulation results demonstrate that the proposed method can achieve high-resolution Inverse Synthetic Aperture Radar (ISAR) images of space group debris in low PRF systems.

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Key wordsAuto-correlation function   Doppler ambiguity   Sparse sample   Group targets of space debris   ISAR imaging     
Received: 2016-01-15; Published: 2016-02-18
Fund:

The National Natural Science Foundation of China (61231017), National Basic Research Program of China (91438106), Shaanxi Youth Science and Technology New Star (2014KJXX-48), Natural Fund of Shaanxi Province (2015JQ6206)

Corresponding Authors: 10.12000/JR16012   
 E-mail: jiang_z_2012@163.com
Cite this article:   
. Space Group Debris Imaging Based on Sparse Sample[J]. JOURNAL OF RADARS, 2016, 5(1): 82-89.
 
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[1] Hu Cheng, Liu Changjiang, Zeng Tao. Bistatic Forward Scattering Radar Detection and Imaging[J]. JOURNAL OF RADARS, 2016, 5(3): 229-243.
[2] Tian Rui-qi, Bao Qing-long, Wang Ding-he, Chen Zeng-ping. An Algorithm for Target Parameter Estimation Based on Fractional Fourier and Keystone Transforms[J]. JOURNAL OF RADARS, 2014, 3(5): 511-517.
 

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