SAR-AIRcraft-1.0:高分辨率SAR飞机检测识别数据集  

SAR-AIRcraft-1.0:High-resolution SAR Aircraft Detection and Recognition Dataset

作　　者：王智睿 康玉卓 曾璇 汪越雷 张汀 孙显 WANG Zhirui;KANG Yuzhuo;ZENG Xuan;WANG Yuelei;ZHANG Ting;SUN Xian(Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China;University of Chinese Academy of Sciences,Beijing 100049,China;School of Electronic,Electrical and Communication Engineering,University of Chinese Academy of Sciences,Beijing 100049,China;Key Laboratory of Network Information System Technology(NIST),Chinese Academy of Sciences,Beijing 100190,China)

机构地区：[1]中国科学院空天信息创新研究院,北京100094 [2]中国科学院大学,北京100049 [3]中国科学院大学电子电气与通信工程学院,北京100049 [4]中国科学院网络信息体系技术科技创新重点实验室,北京100190

出　　处：《雷达学报（中英文）》2023年第4期906-922,共17页Journal of Radars

基　　金：国家自然科学基金(62076241,62171436)。

摘　　要：针对合成孔径雷达(SAR)图像中飞机散射点离散以及背景强干扰造成虚警的问题,该文提出了一种结合散射感知的SAR飞机检测识别方法。一方面,通过上下文引导的特征金字塔模块来增强全局信息,减弱复杂场景中强干扰的影响,提高检测识别的准确率。另一方面,利用散射关键点对目标进行定位,设计散射感知检测模块实现对回归框的细化校正,增强目标的定位精度。为了验证方法有效性、同时促进SAR飞机检测识别领域的研究发展,该文制作并公开了一个高分辨率SAR-AIRcraft-1.0数据集。该数据集图像来自高分三号卫星,包含4,368张图片和16,463个飞机目标实例,涵盖A220,A320/321,A330,ARJ21,Boeing737,Boeing787和other共7个类别。该文将提出的方法和常见深度学习算法在构建的数据集上进行实验,实验结果证明了散射感知方法的优异性能,并且形成了该数据集在SAR飞机检测、细粒度识别、检测识别一体化等不同任务中性能指标的基准。This study proposes a Synthetic Aperture Radar(SAR)aircraft detection and recognition method combined with scattering perception to address the problem of target discreteness and false alarms caused by strong background interference in SAR images.The global information is enhanced through a context-guided feature pyramid module,which suppresses strong disturbances in complex images and improves the accuracy of detection and recognition.Additionally,scatter key points are used to locate targets,and a scatter-aware detection module is designed to realize the fine correction of the regression boxes to improve target localization accuracy.This study generates and presents a high-resolution SAR-AIRcraft-1.0 dataset to verify the effectiveness of the proposed method and promote the research on SAR aircraft detection and recognition.The images in this dataset are obtained from the satellite Gaofen-3,which contains 4,368 images and 16,463 aircraft instances,covering seven aircraft categories,namely A220,A320/321,A330,ARJ21,Boeing737,Boeing787,and other.We apply the proposed method and common deep learning algorithms to the constructed dataset.The experimental results demonstrate the excellent effectiveness of our method combined with scattering perception.Furthermore,we establish benchmarks for the performance indicators of the dataset in different tasks such as SAR aircraft detection,recognition,and integrated detection and recognition.

关 键 词：合成孔径雷达 公开数据集 SAR飞机检测 飞机识别 深度学习 

分 类 号：TP753[自动化与计算机技术—检测技术与自动化装置]