MISSILES AND GUIDANCE TECHNOLOGY

Rao-Blackwellised Particle Filter and It's Application in Navigation

  • WANG Zongyuan ,
  • SUN Feng
Expand
  • Harbin Engineering University; Harbin 150001, China

Received date: 2013-04-11

  Online published: 2025-05-26

Abstract

It is to use the certain kind of model with mixed linear and nonlinear state in current navigation. Its characteristic is that measure function is a nonlinear function of some states and state equation is linear or weak nonlinear system of equations. The problem can be solved through marginal particle filter with state decomposition. The problem is solved through state decomposition of Rao-Blackwellised theory, which nonlinear state is got by particle filter. On the basis particle of nonlinear state, marginalize out linear state, which solved analytically through Kalman filter. The article provides theory study and demonstrates the flow of algorithm. With the study of underwater gravity gradient aided navigation, its condition meets on the condition of this method. So give simulation application of it, and have a comparison with APO-PF in the same large initial position error, the result indicates that the algorithm has a high efficient effect on the underwater gravity gradient navigation.

Cite this article

WANG Zongyuan , SUN Feng . Rao-Blackwellised Particle Filter and It's Application in Navigation[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2013 , 33(6) : 153 -155,159 . DOI: 10.15892/j.cnki.djzdxb.2013.06.049

References

[1]
Schon T, Gustafsson F, Nordlund PJ. Marginalized particle filters for mixed linear/nonlinear state space models[J]. IEEE Transactions on Signal Processing, 2005,53 (7): 2279- 2289.
[2]
周翟和, 刘建业, 赖际舟. Rao-Blackwellized 粒子滤波 SINS/GPS 深组合导航系统中的应用研究[J]. 宇航学报, 2009 (2): 515- 520.
[3]
刘繁明, 钱东, 刘超华. 一种人工物理优化的粒子滤波算法. 控制与决策, 2012, 27 (8): 1145– 1156.
[4]
高晓海. 基于粒子滤波的地形辅助导航算法研究[D]. 成都: 电子科技大学, 2011: 44- 46.
[5]
BDO Anderson, JB Moore. Optimal filtering[M]. Prentice Hall, Englewood Cliffs, 1979: 36- 61.
[6]
Gordon NJ, Salmond DJ, Smith A F. Novel approach to nonlinear and non-Gaussian Bayesian state estimation[J]. IEEE Proceedings-F, 1993, 140 (2): 107- 113.
[7]
Per-Johan Nordlund. Sequential Monte Carlo filters and integrated navigation[D/OL]. http://www.control.isy.liu.se/research/reports/LicentiateThesis/Lic945.pdf. 47-48.
[8]
王文晶. 基于重力和环境特征的水下导航定位方法研究[D]. 哈尔滨: 哈尔滨工程大学, 2009: 71- 75.
Outlines

/