北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2014, Vol. 37 ›› Issue (1): 11-15.doi: 10.13190/j.jbupt.2014.01.003

• 论文 • 上一篇    下一篇

双重自适应UKF在SINS初始对准中的应用

门爱东, 姜竹青, 王宇鹏, 黄承恺   

  1. 北京邮电大学 信息与通信工程学院, 北京 100876
  • 收稿日期:2013-05-16 出版日期:2014-02-28 发布日期:2014-01-07
  • 作者简介:门爱东(1966—),男,教授,博士生导师,E-mail:admen@bupt.edu.cn.
  • 基金资助:

    国家自然科学基金项目(61271190)

Application of Dual Adaptive UKF in Initial Alignment of SINS

MEN Ai-dong, JIANG Zhu-qing, WANG Yu-peng, HUANG Cheng-kai   

  1. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2013-05-16 Online:2014-02-28 Published:2014-01-07

摘要:

对无迹卡尔曼滤波(UKF)算法进行了改进,提出一种双重自适应UKF算法. 该算法能缩放噪声、平抑模型噪声;通过监测基于新息特性的自适应矩阵的迹并进行实时修改,达到抑制观测干扰的目的. 仿真结果表明,双重自适应UKF算法对于模型噪声和观测干扰十分敏感,同时具有较强的鲁棒性,能快速对其进行平抑.

关键词: 非线性系统, 双重自适应算法, 无迹卡尔曼滤波, 初始对准

Abstract:

An improved unscented Kalman filter (UKF) algorithm is called dual adaptive UKF. It could not only stabilize model noise by the method of resizing noise, but also inhibit observation interference by monitoring the trace of the adaptive matrix based on innovation characteristics and amending the adaptive matrix in time. Simulation results show that the dual adaptive UKF algorithm is very sensitive to model noise and observation interference. And it has strong robustness which could stabilize the model noise quickly.

Key words: nonlinear system, dual adaptive algorithm, unscented Kalman filter, initial alignment

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