哈尔滨工程大学学报2026，Vol.47Issue(5)：929-940,12.DOI:10.11990/jheu.202601011
自主水下航行器海底地形与重磁场匹配方法
Autonomous underwater vehicle localization via seafloor terrain and geophysical field matching
摘要
Abstract
To overcome these issues,a multi-source fusion matching method based on a Bayesian estimation framework is proposed,unifying terrain and geomagnetic-gravity matching within a single probabilistic model.The approach employs the unscented Kalman filter(UKF)for nonlinear state estimation,enhanced with simulated annealing for online noise covariance adaptation.A triangle descriptor-based graph isomorphism method is designed for robust terrain correspondence extraction,and a fusion error band-constrained strategy is developed for optimal selection in gravity and magnetic matching.The method effectively improves robustness under large initial errors,reduces false associations caused by low overlap or ambiguous anomalies,and enables tight integration and consistent state updates across multi-source data.Simulation results show the proposed method suppresses navigation drift and achieves higher matching success rates and positioning accuracy in complex seafloor settings,offering a reliable solution for long-endurance,high-precision AUV navigation.关键词
自主水下航行器/多源融合定位/贝叶斯估计/点集匹配/三角形描述子/误差带约束/重磁场匹配/模拟退火Key words
autonomous underwater vehicle/multi-source fusion localization/Bayesian estimation/point set matching/triangle descriptor/error band constraint/gravity-magnetic field matching/simulated annealing分类
交通工程引用本文复制引用
程志雄,陈昶雷,董星犴,陶奥飞,李素军,张强,胡庆玉..自主水下航行器海底地形与重磁场匹配方法[J].哈尔滨工程大学学报,2026,47(5):929-940,12.基金项目
国家自然科学基金项目(52431011,52371305) （52431011,52371305）
国家科技重大专项项目. （）
