• 研究探讨 • 上一篇    下一篇

基于光子集成回路的干涉成像技术

余恭敏1,肖爱群2,晋利兵1,童锡良1,周峰1,*   

  1. 1北京空间机电研究所,北京100094
    2北京宇航系统工程研究所,北京100076
  • 收稿日期:2018-09-20 修回日期:2019-01-28 出版日期:2019-04-25 发布日期:2019-03-19
  • 作者简介:余恭敏(1988-),男,博士研究生,yu_568651142@163com,研究方向为遥感器总体设计
  • 基金资助:

    中国空间技术研究院科技委研究发展课题,国防科技创新特区联合资助

Study on interferometric imaging based on photonic integrated circuits

YU Gongmin1,XIAO Aiqun2,JIN Libing1,TONG Xiliang1,ZHOU Feng1,*   

  1. 1Beijing Institute of Space Mechanis & Electricity,Beijing 100094,China
    2Beijing Institute of Astronautical Systems Engineering,Beijing 100076,China
  • Received:2018-09-20 Revised:2019-01-28 Online:2019-04-25 Published:2019-03-19

摘要: 分块式平面侦察成像系统(Segmented Planar Imaging Detector for Electrooptical Reconnaissance, SPIDER)是基于光子集成回路的干涉成像系统,是提高遥感成像分辨率,降低系统加工难度,减少系统体积、质量、功耗的有效手段之一。首先报告了SPIDER研究现状;并对其基本原理与组成进行了研究;建立了基于部分相干光理论的成像模型;研究了基于平衡正交检测的干涉条纹检测方法;分析了成像系统指标体系;最后对SPIDER成像能力进行了仿真验证。结果表明,SPIDER成像系统具有良好的成像效果,在遥感侦察、空间态势感知等领域具有良好应用潜力。

关键词: 干涉成像, 光子集成回路, 部分相干光理论, 光强分布, 傅里叶逆变换

Abstract: The Segmented Planar Imaging Detector for Electrooptical Reconnaissance(SPIDER) system is an interferometric imaging system based on photonic integrated circuits. It is one of the effective means to improve the resolution of remote sensing imaging, decrease the difficulty of system processing, and reduce the size, weight and power. The current research status of SPIDER is reported. The basic principle and composition was also studied. An imaging model was established based on partially coherent light theory. The method of interference fringe detection is studied based on balanced four quadrature detectors. The index system of imaging system was also analyzed.Finally, the SPIDER imaging capability was simulated and verified. Based on the results of simulation, the imaging ability of SPIDER can broaden its application in remote sensing reconnaissance, spatial situation awareness and other fields.

Key words: interferometric imaging, photonic integrated circuits, partially coherent light theory, intensity distribution, inverse Fourier transform