海洋开发与管理2025，Vol.42Issue(1)：52-60,9.
基于UKF的水下装备轨迹估计滤波算法
Trajectory Estimation Filtering Algorithm for Underwater Equipment Based on UKF
摘要
Abstract
The underwater equipment carried by the East China Sea seabed observation network is often lost due to human activities.When solving the trajectory of underwater equipment by in-ertial navigation,the noise caused by the complex ocean environment and sudden motion leads to large calculation errors.Aiming at the limitation that the classic unscented Kalman filter needs accurate noise model and dynamic model to output better filtering results in the trajectory estimation process,an adaptive filtering algorithm based on Sage-Husa unscented Kalman filter is proposed for solving the trajectory of underwater equipment being towed.Firstly,the imple-mentation process of the classic unscented Kalman filter is explained,and the idea of Sage-Husa adaptive adjustment of noise is introduced;then,on this basis,the prediction residual vector is introduced to reduce the influence of gross error on the filtering result,and a tracking factor is introduced to improve the adaptability of the filter to sudden motion;finally,the effectiveness of the algorithm is verified by simulation experiments and towing experiments.The experimental results show that the adaptive filtering algorithm based on Sage-Husa unscented Kalman filter effectively reduces the divergence error caused by the underwater acoustic environment and sudden motion,and improves the positioning accuracy and positioning stability of underwater equipment when being towed.关键词
无迹卡尔曼滤波/自适应滤波算法/水下装备拖行/改进算法Key words
Unscented kalman filter/Adaptive filtering algorithm/Underwater equipment to-wing/Advanced algorithm分类
海洋学引用本文复制引用
陈子越,季福武,周伟..基于UKF的水下装备轨迹估计滤波算法[J].海洋开发与管理,2025,42(1):52-60,9.基金项目
同济大学学科交叉项目(2023-1-ZD-03) （2023-1-ZD-03）
上海科技创新支持项目(2019-jmrh1-kj15) （2019-jmrh1-kj15）
国家重点研发计划资助项目(2018YFC1405803). （2018YFC1405803）
