电子科技2026，Vol.39Issue(9)：13-18,6.DOI:10.16180/j.cnki.issn1007-7820.2026.09.002
基于RVM的无人机轨迹异常检测研究
Research on UAV Trajectory Anomaly Detection Based on RVM
摘要
Abstract
In the field of UAV(Unmanned Aerial Vehicle)anomaly detection,aiming at the problems of un-derfitting and decreased detection accuracy caused by the lack of parameter selection in traditional UAV trajectory anomaly detection algorithms,this study analyzes the correlations among high-dimensional flight data and proposes a UAV trajectory anomaly detection algorithm TADMR(Research on UAV Trajectory Anomaly Detection Based on RVM)based on RVM(Relevance Vector Machine).By designing the trajectory features of unmanned aerial vehi-cles and conducting feature analysis in combination with the random forest algorithm,the features are extracted to form trajectory feature vectors,and an RVM anomaly detection model is constructed.The experimental results show that the anomaly detection accuracy rate of the TADMR algorithm is 94.16%and the recall rate is 96.21%,which is more effective compared with the traditional unmanned aerial vehicle trajectory anomaly detection algorithm.关键词
无人机/模式识别/RVM/特征提取/异常检测/随机森林Key words
UAV/pattern recognition/RVM/feature extraction/anomaly detection/random forest分类
信息技术与安全科学引用本文复制引用
田崇旭,付雄,邓松,张冲标..基于RVM的无人机轨迹异常检测研究[J].电子科技,2026,39(9):13-18,6.基金项目
国家自然科学基金(51977113) （51977113）
国网浙江省电力有限公司科技项目(5211JX240001)National Natural Science Foundation of China(51977113) （5211JX240001）
Science and Technology Project of State Grid Zhejiang Electric Power Co.,Ltd.(5211JX240001) （5211JX240001）
