基于稀疏采样的空间碎片群目标成像方法

朱江; 邓佳欣; 廖桂生; 朱圣棋

doi:10.12000/JR16012

基于稀疏采样的空间碎片群目标成像方法

doi: 10.12000/JR16012

1.
(西安电子科技大学雷达信号处理国家重点实验室西安 710071)
2.
(中国飞行试验研究院西安 710089)

基金项目:

国家自然科学基金重点项目(61231017),国家重大研究计划(91438106),陕西青年科技新星(2014KJXX-48),陕西省自然基金(2015JQ6206)

详细信息

作者简介:
朱江(1989-),男,陕西人,西安电子科技大学博士生,主要从事压缩感知理论、贝叶斯稀疏重构理论、结构稀疏理论、高速运动平台下的目标运动补偿方法及稀疏ISAR成像技术方面研究。E-mail:jiang_z_2012@163.com邓佳欣(1991-),女,陕西人,西安电子科技大学硕士,中国飞行实验研究院助理工程师,主要从事压缩感知理论及其在宽带信号DOA估计、相干源信号DOA估计应用以及空域雷达目标散射特性、航迹拟合等方面研究。E-mail:jxdeng0501@163.com廖桂生(1963-),男,广西人,西安电子科技大学教授,博士生导师,主要从事自适应信号处理、阵列信号处理、信号检测与估计和智能天线信号处理技术方面研究。E-mail:liaogs@xidian.edu.cn朱圣棋(1984-),男,江西人,西安电子科技大学副教授,博士生导师,主要从事机载/星载雷达地面运动目标检测与定位方面研究。E-mail:zhushengqi8@163.com

通讯作者:
朱江jiang_z_2012@163.com

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出版历程
- 收稿日期: 2016-01-15
- 修回日期: 2016-01-28
- 网络出版日期: 2016-02-28

Space Group Debris Imaging Based on Sparse Sample

1.
(National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China)
2.
(China Flight Test Establishment, Xi'an 710089, China)

Funds:

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)

摘要

摘要: 低重频、短数据条件下的雷达成像是比较困难的,同时,星载平台观测的碎片目标多以群目标形式出现。针对窄带条件下的空间碎片群目标成像问题,该文提出了一种基于稀疏重构的空间碎片群目标成像方法。由于空间碎片通常存在高速自旋现象,且碎片之间因质量、密度等物理差异存在明显的转速差,利用观测时间内碎片群的多周期观测数据与转速差异性,结合回波的自相关特性,能有效实现碎片群的转速检测。由于碎片在空域具有强稀疏特性,结合碎片转速,利用观测矩阵抽取数据,可以实现等效插值操作,并且将稀疏重构得到的数据进行重排,即可得到各个目标的像。抽取操作能够一定程度地抑制其他碎片的回波能量,并解决在低重频条件下的多普勒模糊问题。理论分析证明了该文所提方法的有效性,仿真实验表明,该文所提方法能够在低重频条件下实现对碎片群目标的分别成像。
- 自相关函数 /
- 多普勒模糊 /
- 稀疏采样 /
- 空间碎片群目标 /
- ISAR成像
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.
- Auto-correlation function /
- Doppler ambiguity /
- Sparse sample /
- Group targets of space debris /
- ISAR imaging

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参考文献(16)

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