非线性系统确定采样型滤波算法综述

确定采样型滤波包括Unscented卡尔曼滤波（UKF）,中心差分卡尔曼滤波（CDKF）以及容积卡尔曼滤波（CKF）,是一类基于确定解析采样近似方法的非线性次优高斯滤波算法,具有估计精度高、实现简单等优点,已得到国内外学者的广泛关注.在阐述确定采样型滤波基本原理的基础上,详细总结了近年来确定采样型滤波的研究现状,包括各种改进算法和在不同领域的应用情况;然后重点分析了确定采样型滤波所存在的问题;最后展望了其未来发展趋势和研究方向.

Overview of deterministic sampling filtering algorithms for nonlinear system

Deterministic sampling filters,including Unscented Kalman filter(UKF),central difference Kalman filter(CDKF) and cubature Kalman filter(CKF),are a class of nonlinear suboptimal Gaussian filtering algorithms based on deterministic and analytical sampling approximation,which have advantages of high precision and simple implementation,and have been received wide attention from scholars.The basic principle of deterministic sampling filter is described,and its research situation is summarized in detail,including various improved methods and applications in different areas.Then the problems of deterministic sampling filter at present are analyzed and presented.Finally,its development tendency and research orientation are prospected.