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弹箭与制导学报 >

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

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

导弹与制导技术

随机加权自适应滤波及其在组合导航中的应用

  • 阎海峰 ,
  • 魏文辉 ,
  • 赵雪华 ,
  • 高朝晖 ,
  • 高社生
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  • 西北工业大学自动化学院,西安 710072

阎海峰(1964-),男,陕西户县人,高级工程师,博士研究生,研究方向:导航制导与控制。

收稿日期: 2016-12-08

  网络出版日期: 2025-05-22

基金资助

国家自然科学基金(61174193)

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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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摘要

为了克服自适应Kalman滤波的缺点,文中提出了一种噪声有限记忆在线随机加权自适应滤波算法。在该算法中,利用随机加权和移动开窗方法分别对系统量测噪声和状态噪声的统计特性进行在线随机加权估计,并应用随机加权自适应因子进行调节,控制量测噪声和状态噪声对滤波解算精度的影响。仿真结果表明,在系统噪声统计未知情况下,所提出的噪声有限记忆在线随机加权自适应滤波算法精度明显优于传统Sage自适应Kalman滤波算法。

关键词： 自适应 Kalman 滤波; 随机加权估计; 随机加权自适应滤波; 深组合导航

本文引用格式

阎海峰 , 魏文辉 , 赵雪华 , 高朝晖 , 高社生 . 随机加权自适应滤波及其在组合导航中的应用[J]. 弹箭与制导学报, 2017 , 37(5) : 1 -5,10 . DOI: 10.15892/j.cnki.djzdxb.2017.05.001

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

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