弹道学报2025，Vol.37Issue(4)：112-120,9.DOI:10.12115/ddxb.2025.04004
基于自适应变分贝叶斯UKF的高动态三维目标跟踪方法
High-dynamic Three-dimensional Target Tracking Method Based on Adaptive Variational Bayesian UKF
摘要
Abstract
Under highly dynamic conditions involving high-speed moving targets or rapidly changing system states,the uncertainty of the system model and the complexity of measurement noise increase significantly.Conventional Kalman-type filters based on linear or fixed-noise assumptions often fail to achieve stable estimation accuracy.To address the issues of model nonlinearity and noise uncertainty in three-dimensional tracking of high-dynamic artillery shells,based on an adaptive variational Bayesian(VB),unscented Kalman filter(UKF)with an inverse-Wishart prior distribution was proposed in this paper.The proposed method integrates the VB inference framework with the UKF through a nonlinear correction mechanism,and establishes an adaptive iterative strategy guided by the convergence criterion of filtering.This design enables the online estimation of both process and measurement noise covariances,thus improving robustness against non-stationary and uncertain noise.Furthermore,a modified covariance propagation was introduced to ensure consistency between state prediction and the dynamically updated noise statistics.Simulation experiments were conducted under three-typical noise environments:Gaussian,time-varying,and outlier-contaminated conditions with comparisons against conventional UKF,Sage-Husa UKF,and VB-UKF algorithms.The results demonstrate that the proposed method achieves stable convergence and superior tracking accuracy.Under outlier contamination,it improves position estimation accuracy by approximately 15.3％over the best-performing benchmark algorithm,maintaining strong adaptability and robustness under time-varying and abrupt disturbances noise environments.关键词
高动态炮弹/目标跟踪/自适应滤波/变分贝叶斯Key words
high-dynamic projectile/target tracking/adaptive filter/variational bayesian分类
交通工程引用本文复制引用
李继旭,杨力,郑文杰,汪进文..基于自适应变分贝叶斯UKF的高动态三维目标跟踪方法[J].弹道学报,2025,37(4):112-120,9.基金项目
国家自然科学基金青年基金(62403243) （62403243）
中国科协青年人才托举(2023QNRC001) （2023QNRC001）
国家自然科学基金基础科学中心项目(62388101) （62388101）
中央高校基本科研业务费专项资金资助(30924010931) （30924010931）
