控制与信息技术Issue(5)：1-14,14.DOI:10.13889/j.issn.2096-5427.2025.05.100
非高斯系统鲁棒自适应估计方法综述
A Review of Robust Adaptive Estimation Methods for Non-Gaussian Systems
摘要
Abstract
State estimation is a fundamental component of modern control and information fusion systems,with accuracy and robustness critical to the overall stability and reliability of these systems.In practical applications,system noise often exhibits non-Gaussian characteristics—such as pulses,heavy-tails,and skewness—which lead conventional state estimation methods based on Gaussian assumptions to suffer marked performance degradation when used in non-Gaussian systems.Consequently,robust and adaptive estimation methods for non-Gaussian systems have become a key research focus in this field.This paper provides a systematic review of progress in this area,examines challenges encountered in related industries,and highlights future research directions.It first analyzes the intrinsic characteristics of non-Gaussian noise and how they impact state estimation.It then surveys mainstream approaches from two perspectives—robustness-driven methods and adaptivity-driven methods—focusing on their underlying principles,recent advances,and integration strategies.Particular attention is given to the development of kernel functions and adaptive kernel-width techniques in filters based on the maximum correntropy criterion,as well as to adaptive frameworks such as variational Bayesian inference.Finally,based on the limitations of existing methods,future research directions for state estimation methods in non-Gaussian systems are outlined with respect to generalization capability,computational efficiency and real-time performance,interpretability,and engineering standardization.关键词
非高斯系统/状态估计/鲁棒估计/自适应滤波/最大相关熵准则Key words
non-Gaussian system/state estimation/robust estimation/adaptive filtering/maximum correntropy criterion分类
信息技术与安全科学引用本文复制引用
葛泉波,白雪飞,张宇康,陆振宇..非高斯系统鲁棒自适应估计方法综述[J].控制与信息技术,2025,(5):1-14,14.基金项目
国家自然科学基金重点项目(62033010) （62033010）
浙江省自然科学基金联合基金重大项目(ZJMD25D050002) （ZJMD25D050002）
江苏省青蓝工程项目(R2023Q07) （R2023Q07）
