全球导航卫星系统拒止条件下无人机影像快速级联检索方法  

Fast Cascade Retrieval Method for UAV Images with GNSS Rejection

作　　者：高寒 于英[1] 李力[1] 李磊[1] 宋亮 张磊[1] Gao Han;Yu Ying;Li Li;Li Lei;Song Liang;Zhang Lei(School of Geospatial Information,Information Engineering University,Zhengzhou 450001,Henan,China;Troop 31016,Beijing 100000,China)

机构地区：[1]信息工程大学地理空间信息学院,河南郑州450001 [2]31016部队,北京100000

出　　处：《光学学报》2024年第24期259-268,共10页Acta Optica Sinica

基　　金：国家自然科学基金(42071340);嵩山实验室项目(221100211000-01)。

摘　　要：提出一种全球导航卫星系统(GNSS)拒止条件下的无人机影像快速级联检索方法。基于影像的全局特征,利用哈希小波方法,根据相似度对无人机和卫星影像进行初次检索、筛选和重排序;根据SuperPoint网络设计轻量化特征提取网络(ISFFRN),基于一次检索结果和影像局部特征进行二次检索和排序,以精准筛选目标影像。选用NVIDIA Jetson AGX Orin模拟无人机机载处理设备,在公开的Inria航空影像数据集上开展实验验证。实验结果表明,所提出的级联检索方法在实验区域内能够高效、准确地完成异源影像的快速检索任务,检索过程耗时少于0.5 s,具备满足机载GNSS设备射频广播频率的实时化应用潜力。Objective Our research is of great importance for improving the autonomous positioning ability of UAVs,advancing the development of remote sensing image technology,and enhancing the widespread application of UAVs.Simultaneously,it addresses the challenge of GNSS signal interference,enhances the accuracy and efficiency of image retrieval,and meets the realtime processing needs of UAVs.In complex environments where GNSS signals are disrupted or rejected,traditional positioning methods prove ineffective.The fast cascade retrieval method we proposed significantly strengthens retrieval accuracy and efficiency by comprehensively utilizing local image features and adopting a twolevel retrieval strategy.The method demonstrates feasibility and practicality in realtime processing,which provides reliable positioning support for UAVs in surveying and mapping,firefighting,agriculture,transportation,rescue,and military applications.This research holds crucial practical significance and immediate necessity.Methods We propose a fast cascade retrieval method for UAV images under GNSS rejection conditions,which achieves rapid positioning through a twostage retrieval process(Fig.1).Initially,a subset of aerial image datasets from Vienna,Austria,and Chicago,USA,along with corresponding commercial satellite image data,is selected for the experiment.To ensure data consistency and comparability,these images are cropped and sizenormalized for subsequent retrieval.Subsequently,hash codes and feature point data are extracted from satellite images to construct hash and feature point databases,respectively,thereby improving retrieval efficiency and avoiding redundant calculations.In the initial retrieval stage,the wavelet hashing method is employed by incorporating spatial information.This method extracts lowfrequency spatial components from the image using wavelet transform,generates hash codes,and utilizes these codes for rapid retrieval.The specific steps are as follows.First,the satellite image undergoes wavelet transformation to extrac

关 键 词：全球导航卫星系统拒止 遥感影像检索 异源遥感影像 无人机 

分 类 号：P407.8[天文地球—大气科学及气象学]