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兵工学报 ›› 2013, Vol. 34 ›› Issue (1): 72-75.doi: 10.3969/j.issn.1000-1093.2013.01.013

• 研究论文 • 上一篇    下一篇

基于粒子滤波衰减因子抑制干扰的组合导航信息融合算法

  

  1. 1北京理工大学 机电工程学院, 北京 100081; 2哈尔滨建成集团有限公司, 黑龙江 哈尔滨 150030; 3空军装备研究院 总体所,  北京 100076; 4驻624厂军事代表室, 黑龙江 哈尔滨 150030
  • 上线日期:2013-07-22

Information Fusion Algorithm for Integrated Navigation System with Suppressing Interference of Particle Filters Fading Factors

  1. 1School of Mechatronics Engineering, Beijing Institute of Technology, Beijing 100081, China; 2Harbin Jiancheng Group Co Ltd, Harbin 150030, Heilongjiang, China; 3Institute of Macro Demonstration, Equipment Academy of Air Force, Beijing 100076, China; 4Military Representative Office in 624 Factory, Harbin 150030, Heilongjiang, China
  • Online:2013-07-22

摘要:

为修正组合导航系统受到干扰的数据,使用粒子滤波算法判别数据是否符合系统误差要求;采用改进的粒子滤波算法,当组合导航系统单一通道受到干扰而发散时,通过改变受干扰通道粒子在系统中的权值来抑制干扰。仿真结果表明,改进的粒子滤波算法在组合导航系统单一通道发散的条件下能够有效地降低误差、提高精度,从而使系统仍能保持较好的工作状态。

关键词: 兵器科学与技术, 贝叶斯理论, 粒子滤波, 权值, 似然函数

Abstract:

To revise the interference statistics of an integrated navigation system, a particle filtering algorithm was adopted to discriminate the systematic error of the statistics. And the modified particle filtering algorithm changes the weights of particles to suppress the interference when a single channel subjects to interference and tends to divergence. The simulation results show that the modified particle filtering algorithm is able to keep the system even for the divergence of a superior function by reducing the error efficiently and increasing the accuracy.

Key words: ordnance science and technology, Bayes theory, particle filter, weight value, likelihood function