摘要
目标检测与识别是高分辨合成孔径雷达(SAR)领域的热点问题。机场上飞机作为一种典型目标,其检测和识别有一定的独特性。该文回顾了SAR图像典型目标检测识别领域技术的发展过程,分析了SAR图像中飞机目标的散射机制及面临的技术难点,阐述了SAR飞机目标检测识别的系统流程、技术路线和关键科学问题,对基于传统与基于深度学习两个方面的飞机目标检测识别的研究进展进行了归纳总结,并讨论了各类方法的特点及存在的问题,展望了未来的发展趋势。该文认为如何将深度学习与目标电磁散射机理结合、提高网络或模型的泛化能力是提升SAR图像中目标检测识别精度的关键,并给出了一种基于散射信息与深度学习融合的飞机目标检测方法。
Target detection and recognition are popular issues in the field of high-resolution Synthetic Aperture Radar(SAR).As a typical target,aircraft detection and identification has certain uniqueness.This paper reviews the development of detection and recognition techniques for a typical target in SAR imagery,analyzes the scattering mechanism and technical difficulties of aircraft in SAR imagery,describes the system flow,technical routes,and key scientific problems of target aircraft detection and recognition in SAR imagery,summarizes the research progress from traditional methods to deep-learning-based methods for aircraft detection and recognition,discusses the characteristics and existing problems of various methods,and predicts the future development trend.This paper proposes that combining target electromagnetic scattering mechanism with deep convolutional neural network to improve the generalization capability of the model is the key to improve SAR detection and recognition performance.Moreover,this paper establishes an aircraft detection method based on the fusion of scattering information and deep convolutional neural network.
作者
郭倩
王海鹏
徐丰
GUO Qian;WANG Haipeng;XU Feng(Key Laboratory for Information Science of Electromagnetic Waves,Fudan University,Shanghai 200433,China)
出处
《雷达学报（中英文）》
CSCD
北大核心
2020年第3期497-513,共17页
Journal of Radars
基金
国家自然科学基金(61991422)。
关键词
合成孔径雷达
飞机检测
飞机识别
散射信息
深度学习
Synthetic Aperture Radar(SAR)
Aircraft detection
Aircraft recognition
Scattering information
Deep learning
