微波视觉与SAR图像智能解译

徐丰 金亚秋

徐丰, 金亚秋. 微波视觉与SAR图像智能解译[J]. 雷达学报(中英文), 2024, 13(2): 285–306. doi: 10.12000/JR23225
引用本文: 徐丰, 金亚秋. 微波视觉与SAR图像智能解译[J]. 雷达学报(中英文), 2024, 13(2): 285–306. doi: 10.12000/JR23225
XU Feng and JIN Yaqiu. Microwave vision and intelligent perception of radar imagery[J]. Journal of Radars, 2024, 13(2): 285–306. doi: 10.12000/JR23225
Citation: XU Feng and JIN Yaqiu. Microwave vision and intelligent perception of radar imagery[J]. Journal of Radars, 2024, 13(2): 285–306. doi: 10.12000/JR23225

微波视觉与SAR图像智能解译

doi: 10.12000/JR23225
基金项目: 国家自然科学基金(61991422)
详细信息
    作者简介:

    徐 丰,博士,教授,主要研究方向为SAR图像解译、电磁散射建模、人工智能等

    金亚秋,博士,教授,中国科学院院士,主要研究方向为复杂自然环境与目标电磁散射辐射传输、空间微波遥感和计算电磁

    通讯作者:

    徐丰 fengxu@fudan.edu.cn

  • 责任主编:仇晓兰 Corresponding Editor: QIU Xiaolan
  • 中图分类号: TN957.51

Microwave Vision and Intelligent Perception of Radar Imagery

Funds: The National Natural Science Foundation of China (61991422)
More Information
  • 摘要: 高分辨率雷达成像技术和人工智能、大数据技术的快速发展,有力促进了雷达图像智能解译技术的进步。由于雷达传感器本身的特殊性和电磁散射成像物理的复杂性,雷达图像的解译缺乏光学图像的直观性,准确迅速识别分类的需求对雷达图像解译提出了迫切的挑战。在借鉴人脑光视觉感知机理和计算机视觉图像处理相关技术基础上,进一步融合电磁散射物理规律及其雷达成像机理,我们提出发展微波域雷达图像解译的“微波视觉”的新交叉领域研究。该文介绍微波视觉的概念与内涵,提出微波视觉认知模型,阐述其基础理论问题与技术路线,最后介绍了作者团队在相关问题上的初步研究进展。

     

  • 图  1  微波视觉概念示意图

    Figure  1.  Concept of microwave vision

    图  2  同一目标在光学图像和SAR图像上的特点对比

    Figure  2.  Comparision of the characteristics of the same targets in optical and SAR images

    图  3  光学视觉认知规律在微波图像域将失效

    Figure  3.  Visual perceptual rules become invalid in the microwave image domain

    图  4  微波视觉与光学视觉的关系

    Figure  4.  Relationship between microwave vision and optical vision

    图  5  微波视觉认知模型

    Figure  5.  The perception model of microwave vision

    图  6  微波视觉的可能实现方法

    Figure  6.  Possible implementations of microwave vision

    图  7  语义电磁散射基本属性与实现途径

    Figure  7.  Basic properties and implementations of semantic electromagnetic scattering model

    图  8  物理先验与神经网络的不同层次融合

    Figure  8.  Fusion of physical priors and neural networks at different levels

    图  9  智能体、模拟器及专家之间的交互模式

    Figure  9.  Interaction modes among agents, simulators, and experts

    图  10  相干散射子基元字典及SAR图像语义表征模式[39]

    Figure  10.  Primitive Scatterer Dictionary (PSD) and semantic representation of SAR images[39]

    图  11  仿真辅助数据增广对于目标分类性能的提升

    Figure  11.  Performance improvements for target classification with simulation-assisted data augmentation

    图  12  SAR图像因果模型

    Figure  12.  Causal model of SAR images

    图  13  SAR-NeRF原理与等价计算图[50]

    Figure  13.  SAR-NeRF principle and the equivalent computation graph[50]

    图  14  可微SAR渲染器(DSR)

    Figure  14.  Differentiable SAR Renderer (DSR)

    图  15  智能体与模拟器交互式反演架构[53]

    Figure  15.  Interactive inversion architecture between agents and simulators[53]

    图  16  智能体与专家交互的人机协同学习模式[38]

    Figure  16.  Human-machine collaborative learning mode with interactions between agents and experts[38]

    表  1  光学图像和SAR图像对比

    Table  1.   Comparison between optical and SAR images

    图像特性 光学图像 SAR图像
    物理特性 波段 可见光波段 微波波段
    探测方式 外界光源、被动接收 主动辐射、后向散射
    反射/散射形态 连续、面状 离散、点状
    成像机制 聚焦机制 真实孔径 相干合成孔径
    随机噪声 加性噪声 乘性相干斑
    投影方式 透视投影 斜距投影
    投影方向 俯仰角-方位角 距离向-方位向
    图像形态 图像畸变效应 透视效应,分辨率与距离成正比 收缩、叠掩、倒置,分辨率与距离无关
    目标与场景呈现方式 自然图像:人眼视角、大目标小背景 遥感图像:鹰眼视角、大背景小目标
    数据形式 颜色、强度 相位、幅度、极化
    下载: 导出CSV

    表  2  微波视觉认知模型中的基本概念

    Table  2.   Notations of the perception model of microwave vision

    概念 定义 举例
    目标语义知识 $ k{\text{~}}{P}_{k}\left(k\right)\in {\mathbb{C}}^{{N}_{k}} $ 目标型号:T72, BTR60 ···
    目标多样性 $ d{\text{~}}{P}_{d}\left(d\right)\in {\mathbb{C}}^{{N}_{d}} $ 细节变化、个体差异、背景环境···
    目标物理信息 $ x{\text{~}}{P}_{x}\left(x\right)\in {\mathbb{R}}^{{N}_{x}} $ 目标几何模型、表面材质···
    观测数据 $ y{\text{~}}{P}_{y}\left(y\right)\in {\mathbb{R}}^{{N}_{y}} $ SAR图像
    观测配置 $ \theta $ 波段、入射角、分辨率···
    观测噪声 $ \delta $ 传感器噪声、测量误差、模型误差···
    下载: 导出CSV
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  • 收稿日期:  2023-11-21
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