Thermal sentinel: Low-earth orbit infrared intelligent system for flying civil aircraft safety

IF 11.4 1区地球科学 Q1 ENVIRONMENTAL SCIENCES

Remote Sensing of Environment Pub Date : 2025-06-13 DOI:10.1016/j.rse.2025.114826

Liyuan Li , Xiaoxuan Zhou , Wencong Zhang , Yifan Zhong , Long Gao , Jianing Yu , Xiaoyan Li , Fansheng Chen

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引用次数: 0

Abstract

The surveillance and detection of civil aircraft over a wide area has long been a technical challenge, with no available datasets and complete detection methods yet. The first global space-based three-channels thermal infrared flying civil aircraft dataset (TIFAD.v1) is established by this paper, covering 17 months, six continents, with 21,004 aircraft and 1252 contrail aircraft, integrating ADS-B civil aviation data. TIFAD.v1 is a fine-grained dataset of small flying targets with aircraft type, calibrated altitude, ground speed, and track. We investigates the radiative feature of high-altitude flying targets and finds that their thermal radiation peaks are primarily distributed in the 10.3–12.5 μm band. Additionally, a significant altitude-dependent difference in transmittance is observed at 11.72 μm, which helps suppress background interference and enhances the reliability of target detection. And an innovative detection method for wide-area flying target is developed, combined YOLOv11n-based deep learning algorithms with in-situ radiative characteristics including the top of atmosphere radiance, temperature contrast, SCR to enhance detection accuracy. This technology provides an effective and robust new approach for all-weather detection of maneuverable flight targets on a global scale, demonstrating the significant potential of intelligent technology in the field of thermal infrared remote sensing applications. Moreover the in situ data allows for quantitative measurement of the radiative feature of flight targets, providing essential data for research on infrared and atmospheric transmittance.

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热哨：用于民用飞机安全飞行的近地轨道红外智能系统

长期以来，在大范围内对民用飞机进行监视和检测一直是一项技术挑战，目前还没有可用的数据集和完整的检测方法。本文建立了全球首个天基三通道热红外飞行民用飞机数据集（TIFAD.v1），涵盖17个月，6大洲，21004架飞机和1252架航迹飞机，整合ADS-B民航数据。TIFAD。V1是一个细粒度的小型飞行目标数据集，包含飞机类型、校准高度、地面速度和航迹。研究了高空飞行目标的辐射特征，发现其热辐射峰主要分布在10.3 ~ 12.5 μm波段。此外，在11.72 μm处，透射率随高度有显著差异，这有助于抑制背景干扰，提高目标检测的可靠性。提出了一种基于yolov11n的广域飞行目标创新检测方法，将yolov11n深度学习算法与大气顶辐度、温度对比、可燃比等现场辐射特性相结合，提高了广域飞行目标的检测精度。该技术为全球范围内机动飞行目标的全天候探测提供了一种有效、稳健的新方法，显示了智能技术在热红外遥感应用领域的巨大潜力。此外，现场数据允许对飞行目标的辐射特性进行定量测量，为红外和大气透射率的研究提供必要的数据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Remote Sensing of Environment 环境科学-成像科学与照相技术

CiteScore

25.10

自引率

8.90%

发文量

455

审稿时长

53 days

期刊介绍： Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.