{"title":"Application of Nonlinear H∞ Filtering Algorithm for Initial Alignment of the Missile-borne SINS","authors":"Zhiqiang Wu, Yu Wang, Xinhua Zhu","doi":"10.1016/j.aasri.2014.09.017","DOIUrl":null,"url":null,"abstract":"<div><p>The H∞ filtering and Unscented Transformation(UT) algorithm are introduced to deal with the initial alignment error of missile-borne Strapdown Inertial Navigation System(SINS), which is caused by the nonlinear error model and the uncertainty of the disturbance noise. Firstly, on the basis of additional quaternion error, the error model of SINS is built up. Secondly, the nonlinear H∞ filter based on UT and H∞ filtering is constructed, which is with nonlinear approximation ability and strong robustness. Finally, simulations are made compared with UKF and the nonlinear H∞ filter under the conditions of disturbance model of strong wind. The result shows that nonlinear H∞ filter is more stable and faster than UKF under the disturbance conditions of strong wind and can effectively improve the accuracy of initial alignment and robustness of the algorithm.</p></div>","PeriodicalId":100008,"journal":{"name":"AASRI Procedia","volume":"9 ","pages":"Pages 99-106"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.aasri.2014.09.017","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AASRI Procedia","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212671614001176","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The H∞ filtering and Unscented Transformation(UT) algorithm are introduced to deal with the initial alignment error of missile-borne Strapdown Inertial Navigation System(SINS), which is caused by the nonlinear error model and the uncertainty of the disturbance noise. Firstly, on the basis of additional quaternion error, the error model of SINS is built up. Secondly, the nonlinear H∞ filter based on UT and H∞ filtering is constructed, which is with nonlinear approximation ability and strong robustness. Finally, simulations are made compared with UKF and the nonlinear H∞ filter under the conditions of disturbance model of strong wind. The result shows that nonlinear H∞ filter is more stable and faster than UKF under the disturbance conditions of strong wind and can effectively improve the accuracy of initial alignment and robustness of the algorithm.