基于红外偏振成像的复杂干扰环境下无人机目标检测方法

乔新博; 郭阳; 赵永强; 刘亮

doi:10.12263/DZXB.20250496

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基于红外偏振成像的复杂干扰环境下无人机目标检测方法

学术论文 | 更新时间：2026-02-10

- 基于红外偏振成像的复杂干扰环境下无人机目标检测方法
- An Infrared Polarization Based UAV Detection Method for Complex Environment
- 电子学报 2025年53卷第11期页码：3920-3931
- 作者机构：
  
  1.西北工业大学自动化学院，陕西西安 710072
  2.中国人民解放军海军航空大学，山东烟台 264001
- 作者简介：
  
  [ "乔新博男，1999年2月出生于黑龙江省哈尔滨市.现为西北工业大学博士研究生.主要研究方向为红外偏振成像及其应用.E-mail: qxinbo@foxmail.com" ]
  [ "郭阳男，1990年1月出生于宁夏回族自治区银川市. 现为西北工业大学博士研究生.主要研究方向为图像处理与传感器设计.E-mail: guoyang665@mail.nwpu.edu.cn" ]
  [ "赵永强男，1976年7月出生于陕西省西安市.现为西北工业大学自动化学院教授、博士生导师.主要研究方向为信息融合、图像处理、偏振成像等.获中国专利奖、省部级科技进步奖等奖项10项. 在国内外发表学术论文100余篇.E-mail: zhaoyq@nwpu.edu.cn" ]
  [ "刘亮男，1981 年2月出生于湖北省黄石市.现为海军航空大学副教授.主要研究方向为激光技术与红外技术.E-mai1: liul513@126.com" ]
- 基金信息：
  
  国家自然科学基金(61771391);深圳市科技重大专项(KJZD20230923114159039)
- DOI：10.12263/DZXB.20250496
  中图分类号： TN219;
- 收稿：2025-06-09，
  
  录用：2025-11-10，
  
  纸质出版：2025-11-25
- 稿件说明：
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乔新博, 郭阳, 赵永强, 等. 基于红外偏振成像的复杂干扰环境下无人机目标检测方法[J]. 电子学报, 2025, 53(11): 3920-3931.

QIAO Xin-bo, GUO Yang, ZHAO Yong-qiang, et al. An Infrared Polarization Based UAV Detection Method for Complex Environment[J]. Acta Electronica Sinica, 2025, 53(11): 3920-3931.
乔新博, 郭阳, 赵永强, 等. 基于红外偏振成像的复杂干扰环境下无人机目标检测方法[J]. 电子学报, 2025, 53(11): 3920-3931. DOI：10.12263/DZXB.20250496

QIAO Xin-bo, GUO Yang, ZHAO Yong-qiang, et al. An Infrared Polarization Based UAV Detection Method for Complex Environment[J]. Acta Electronica Sinica, 2025, 53(11): 3920-3931. DOI：10.12263/DZXB.20250496

摘要

现有雷达、射频、光学等探测手段在复杂干扰环境中检测无人机时存在误警率高、检测精度低等问题.针对这些问题，本文利用无人机与背景红外辐射偏振信息差异较大的特点，提出基于分焦平面红外偏振成像的复杂干扰环境无人机目标检测方法.该方法构建了一个基于注意力机制与去马赛克蒸馏的目标检测网络（Attention Network with Distillation Demosaic，ANDD），可直接以分焦平面偏振相机获取的偏振马赛克图像为输入，实现对无人机目标的高精度实时检测.首先设计预训练偏振解码蒸馏网络（Polarization DeMosaic Distillation Network，PDMDN）从偏振马赛克图像中快速获取噪声较少的多维偏振信息；其次，使用骨干网络从多维偏振信息中提取目标的纹理、形状等初步特征；最后，建立偏振注意力特征（Polarization ATtention，PAT），利用多维偏振信息实现复杂干扰环境无人机目标检测.为评估算法性能，基于分焦平面红外偏振成像系统建立了复杂干扰环境下无人机目标检测数据集，并在该数据集上与近年最先进的6种目标检测方法进行了比较，验证了本文算法的有效性.

Abstract

While detecting UAV under complex interferences

the existing methods based on radar

radio frequency and vision system obtains a high false alarm rate and low accuracy. Aimed at these problems

an UAV detection method for complex scenes is constructed based on the infrared division of focal plane (DoFP) polarization imager. By utilizing the polarization difference between UAV and background

the constructed attention network with distillation demosaic (ANDD) directly obtains the detection result from the mosaic image obtained from the DoFP imager with high accuracy in real time. Firstly

the method constructs the multi-polarized information with low noise using the pretrained polarization demosaic distillation network (PDMDN). Then

the primary features are extracted from the backbone network. Finally

the polarization attention (PAT) network is designed to obtain the UAV detection result by further applying the polarized feature. To verify the efficiency of our proposed ANDD network

an infrared polarization UAV detection dataset with complex interferences is constructed using an infrared DoFP imager. Experiences with the state-of-the-art methods demonstrate that the proposed method obtains a considerable result

demonstrate the effectiveness of the ANDD method.

关键词

Keywords

references

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