{"title":"自组织模型非线性卡尔曼滤波","authors":"","doi":"10.36652/0869-4931-2021-75-2-73-78","DOIUrl":null,"url":null,"abstract":"To improve the accuracy of the aircraft navigation system error correction in the output signal is used. The errors of the navigation complex are estimated by using a nonlinear Kalman filter. It is proposed to use a nonlinear model constructed by the method of self-organization as a model of the process being evaluated. The effectiveness of the self-organization algorithm in comparison with the genetic algorithm and the neural network is confirmed by the results of mathematical modeling.\n\nKeywords\naircraft; inertial navigation system; error model; self-organization algorithm","PeriodicalId":309803,"journal":{"name":"Automation. Modern Techologies","volume":"710 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Nonlinear Kalman filter with self-organizing model\",\"authors\":\"\",\"doi\":\"10.36652/0869-4931-2021-75-2-73-78\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To improve the accuracy of the aircraft navigation system error correction in the output signal is used. The errors of the navigation complex are estimated by using a nonlinear Kalman filter. It is proposed to use a nonlinear model constructed by the method of self-organization as a model of the process being evaluated. The effectiveness of the self-organization algorithm in comparison with the genetic algorithm and the neural network is confirmed by the results of mathematical modeling.\\n\\nKeywords\\naircraft; inertial navigation system; error model; self-organization algorithm\",\"PeriodicalId\":309803,\"journal\":{\"name\":\"Automation. Modern Techologies\",\"volume\":\"710 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Automation. Modern Techologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36652/0869-4931-2021-75-2-73-78\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automation. Modern Techologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36652/0869-4931-2021-75-2-73-78","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Nonlinear Kalman filter with self-organizing model
To improve the accuracy of the aircraft navigation system error correction in the output signal is used. The errors of the navigation complex are estimated by using a nonlinear Kalman filter. It is proposed to use a nonlinear model constructed by the method of self-organization as a model of the process being evaluated. The effectiveness of the self-organization algorithm in comparison with the genetic algorithm and the neural network is confirmed by the results of mathematical modeling.
Keywords
aircraft; inertial navigation system; error model; self-organization algorithm