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Journal of Projectiles, Rockets, Missiles and Guidance >

2017 , Vol. 37 >Issue 5: 1 - 5,10

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2017.05.001

MISSILES AND GUIDANCE TECHNOLOGY

Random Weighting Adaptive Filtering and Its Application inIntegrated Navigation

  • YAN Haifeng ,
  • WEI Wenhui ,
  • ZHAO Xuehua ,
  • GAO Zhaohui ,
  • GAO Shesheng
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  • School of of Automation, Northwestern Polytechnical University, Xi'an 710072, China

Received date: 2016-12-08

  Online published: 2025-05-22

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Abstract

In order to overcome the shortcomings of the adaptive Kalman filtering, an adaptive filtering algorithm based on adaptive noise limited memory is proposed. In this algorithm, based on the system measurement noise and state noise statistical characteristics, the author adopted the online random weighting estimation. And the random weighting adaptive factor was adjusted to control the influence of the measurement noise and the state noise on the accuracy of the filter. The simulation results showed that the accuracy of the proposed algorithm is superior to the traditional Sage adaptive Kalman filtering algorithm in the condition of the system with unknown noise statistics.

Key words： adaptive Kalman filter; random weighting estimation; random weighting adaptive filter; deep combination navigation

Cite this article

YAN Haifeng , WEI Wenhui , ZHAO Xuehua , GAO Zhaohui , GAO Shesheng . Random Weighting Adaptive Filtering and Its Application inIntegrated Navigation[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2017 , 37(5) : 1 -5,10 . DOI: 10.15892/j.cnki.djzdxb.2017.05.001

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