系统工程与电子技术 ›› 2020, Vol. 42 ›› Issue (10): 2197-2206.doi: 10.3969/j.issn.1001-506X.2020.10.07

• 传感器与信号处理 • 上一篇    下一篇

机动平台大斜视压缩感知SAR成像方法

马彦恒(), 李根(), 熊旭颖(), 侯建强()   

  1. 陆军工程大学石家庄校区无人机工程系, 河北 石家庄 050003
  • 收稿日期:2020-01-06 出版日期:2020-10-01 发布日期:2020-09-19
  • 作者简介:马彦恒(1968-),男,教授,博士研究生导师,博士,主要研究方向为机动SAR成像、低小慢目标探测等方向的研究。E-mail:mamyh11@126.com|李根(1991-),男,博士研究生,主要主要研究方向为机动平台大斜视SAR成像和压缩感知雷达成像研究。E-mail:radarlg@126.com|熊旭颖(1998-),女,硕士研究生,主要主要研究方向为曲线轨迹SAR成像研究。E-mail:307708608@qq.com|侯建强(1991-),男,博士,主要主要研究方向为曲线SAR三维成像研究。E-mail:1052503919@qq.com
  • 基金资助:
    “十三五”军队“双重”学科建设项目资助课题

High-squint compressed sensing SAR imaging mounted on maneuvering platform

Yanheng MA(), Gen LI(), Xuying XIONG(), Jianqiang HOU()   

  1. Department of UAV Engineering, Army Engineering University Shijiazhuang Campus, Shijiazhuang 050003, China
  • Received:2020-01-06 Online:2020-10-01 Published:2020-09-19
  • Supported by:
    “十三五”军队“双重”学科建设项目资助课题

摘要:

为降低合成孔径雷达(synthetic aperture radar, SAR)成像系统的数据量并提高其平台适应性,提出了一种基于频域近似观测算子的机动平台大斜视压缩感知SAR成像方法。在构建近似观测算子的过程中,首先,基于等斜视角曲线构建了一种能够精确描述地面散射点成像参数空变性的斜距模型。然后,引入距离走动校正函数和高阶时域扰动因子实现了距离方位的解耦和空变距离徙动的校正,并通过构建时频域的相位滤波因子校正了方位压缩参数的空变性。最后,采用复近似信息传递(complex approximation message passing, CAMP)算法对稀疏和非稀疏场景进行快速、高精度重建。该方法通过校正成像参数的空变性,提高了近似观测算子的精度,实现了扩展场景的机动平台大斜视压缩感知SAR成像,仿真结果支撑了理论分析并验证了所提方法的有效性。

关键词: 合成孔径雷达成像, 压缩感知, 机动平台, 大斜视

Abstract:

To reduce the data volume of the synthetic aperture radar (SAR) imaging system and improve its platform adaptability, a novel frequency-domain approximated observation based high-squint compressed sensing SAR imaging method mounted on maneuvering platforms is proposed. First, a slant range model based on the equal-squint-angle curve is constructed to accurately describe the spatial variability of imaging parameters for the ground scattering point. Then, the range-azimuth decoupling and the spatial-variant range cell migration correcting are realized by introducing the range walk correction function and the high-order time-domain disturbance factor, and the spatial variability of the azimuth compression parameters is corrected by constructing the phase filtering factors in the time and frequency domains. Finally, the complex approximation message passing (CAMP) algorithm is used to obtain fast and high-precision reconstruction of the sparse and non-sparse scene. This method improves the precision of the approximated observation operator by correcting the spatial variability of the imaging parameter, and achieves the high-squint compressed sensing SAR imaging of the extended scene on maneuvering platform. The simulation results support the theoretical analysis and illustrate the effectiveness of the proposed method.

Key words: synthetic aperture radar (SAR) imaging, compressed sensing, maneuvering platform, high-squint

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