BIMSA > Engineering Mathematics Seminar: Fundamentals and Frontiers in Control, Filtering, State Estimation, and Signal Processing Nonlinear Filtering Based on Moment Approximation and Gaussian Approximation
Nonlinear Filtering Based on Moment Approximation and Gaussian Approximation
Organizers
Xiaopei Jiao , Jiayi Kang
Speaker
Sanfeng Hu
Time
Thursday, May 22, 2025 2:30 PM - 4:00 PM
Venue
A3-2-303
Online
Zoom 435 529 7909 (BIMSA)
Abstract
This report investigates the estimation problem for discrete-time nonlinear stochastic dynamic systems. Within the moment approximation framework, a third degree moment-approximation based filtering algorithm is developed using a sequential homotopy method under a linear estimation structure. By propagating higher-order statistical information, the proposed filter improves estimation accuracy and overcomes the limitation of conventional linear estimation-based filters, which can only propagate the first two moments. Within the distribution approximation framework, two Gaussian filtering algorithms are proposed based on the minimization of Kullback-Leibler divergence. These algorithms transcend the constraints of linear estimation frameworks, offering high estimation accuracy while maintaining low computational complexity.
Speaker Intro
Sanfeng Hu received the B.S. degree in computer science and technology, the M.S. degree in applied mathematics, and the Ph.D. degree in mathematical statistics from Sichuan University, Chengdu, China, in 2015, 2018, and 2022, respectively. Since 2022, he has been with the School of Mathematics and Statistics, Yunnan University, Kunming, China, where he is currently a Lecturer. His research interests are in the fields of estimation, target tracking, information fusion, optimization algorithms, and machine learning.