中国科技核心期刊

中文核心期刊

CSCD来源期刊

空间控制技术与应用 ›› 2009, Vol. 35 ›› Issue (1): 30-35.

• 学术研究 • 上一篇    下一篇

近似二阶扩展卡尔曼滤波方法研究

范炜1,2,李勇3   

  1. 1.北京控制工程研究所,北京 100190;
    2.空间智能控制技术国家级重点实验室, 北京 100190 ;
    3.中国空间技术研究院研究发展中心, 北京 100094
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-02-25 发布日期:2009-02-25

A Method of Approximate Second-Order Extended Kalman Filter

FAN Wei 1,2, LI Yong 3   

  1. 1. Beijing Institute of Control Engineering, Beijing 100190, China;
    2.National Laboratory of Space Intelligent Control,Beijing 100190,China;
    3.R&D Center, China Academy of Space Technology, Beijing 100094, China
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-02-25 Published:2009-02-25

摘要: 在综合考虑计算量和估计精度的情况下,提出一种新的非线性滤波方法——近似二阶扩展卡尔曼滤波(AS-EKF)方法。该方法基于线性最小方差递推滤波框架,对均值的非线性变换采用二阶近似,其精度高于扩展卡尔曼滤波(EKF)采用的一阶近似。通过计算机仿真表明该滤波方法对非线性系统的滤波精度高于EKF,且计算量明显低于无迹滤波(UKF),该方法适用于对估计精度和计算量都有所要求的非线性系统滤波器设计。

关键词: 非线性滤波, 扩展卡尔曼滤波, 状态估计

Abstract: A new approach for nonlinear filtering systems is presented in this paper to meet the requirements both on accuracy and computing time. This method, called as approximate second-order extended Kalman filter (AS-EKF), is based on the frame of recursive linear minimum variance estimation. Other than extended Kalman filter (EKF) linearizing all nonlinear models, the new approach estimates the expectation value to the second-order of accuracy. We show that this technique is more accurate than EKF, and it also costs the less computing time than unscented Kalman filter (UKF).It can be used in the nonlinear filtering concerned with both accuracy and computing time.

Key words: nonlinear filtering, extended Kalman filter, state estimation

中图分类号: 

  • O211.64