Research on SINS initial alignment and the methods for the parameter γ Selection Based on H∞ Filtering Technique

Zhang Tao; 徐晓苏

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Research on SINS initial alignment and the methods for the parameter γ Selection Based on H∞ Filtering Technique

更新时间：2023-11-28

- Research on SINS initial alignment and the methods for the parameter γ Selection Based on H∞ Filtering Technique
- Advanced Engineering Sciences Vol. 41, Issue 4, Pages: 240-245(2009)
- 作者机构：
  
  1. 东南大学
  2. 东南大学仪器科学与工程学院江苏,南京,210096
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2009，
  
  Published Online：31 October 2008，
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张涛,徐晓苏.基于H∞的捷联系统初始对准及参数γ选取方法研究[J].工程科学与技术,2009,41(4):240-245.

Zhang Tao, 徐晓苏. Research on SINS initial alignment and the methods for the parameter γ Selection Based on H∞ Filtering Technique. [J]. Advanced Engineering Sciences 41(4):240-245(2009)
张涛,徐晓苏.基于H∞的捷联系统初始对准及参数γ选取方法研究[J].工程科学与技术,2009,41(4):240-245. DOI：

Zhang Tao, 徐晓苏. Research on SINS initial alignment and the methods for the parameter γ Selection Based on H∞ Filtering Technique. [J]. Advanced Engineering Sciences 41(4):240-245(2009) DOI：

摘要

中文摘要: 针对KALMAN滤波在系统模型不确定或噪声统计特性不准确的情况下滤波精度不高甚至发散的问题，引入了H∞滤波技术，介绍了H∞滤波基本理论和递推公式，与KALMAN滤波在本质上做了比较。建立了12维状态量的初始对准模型，在此基础上做了KALMAN滤波和H∞滤波在白噪声条件和有色噪声条件下的对比仿真，为了说明H∞滤波中参数γ的选取对对准速度和精度的影响，还分别选取3个有代表性的参数γ做了对比仿真，仿真结果表明：在白噪声条件下，两种滤波的精度相当，KALMAN滤波相对于H∞滤波要稍好些；在有色噪声条件下，KALMAN滤波显得有些发散，而H∞滤波明显对有色噪声的抗干扰性强于KALMAN滤波。同时通过对参数γ的适当选取，对系统的平均性能（精度）和鲁棒性能进行一定的平衡。

Abstract

Abstract:The H∞ filtering is introduced because KALMAN filtering accuracy is not high or even divergent issues when system model is uncertain or noise statistics characteristics are not accurate. H∞ filtering basic theory and recursive formulas are introduced and compared with KALMAN filtering in essence. The initial alignment model of 12-dimensional states is established and is simulated compared with KALMAN filtering under the conditions of white noise and color noise. Three representative parameters γ were selected for compared simulation in order to illustrate the impact of the selection of γ at the speed and accuracy of initial alignment. The simulation results show that in the circumstances of white noise the accuracy of two filter almost the same but KALMAN filter is slightly better. In the circumstances of color noise the anti-interference of H∞ filter is obviously stronger than KALMAN filter. At the same time

the average performance (accuracy) and robust performance of the system are balanced by selecting the parameter γ properly.

关键词

捷联惯性系统初始对准滤波KALMAN滤波

Keywords

SINSInitial alignmentfilteringKALMAN filtering

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