{"title":"基于RHKF的平台惯性导航系统现场标定","authors":"Fan Mo, Z. Deng, Bo Wang, M. Fu","doi":"10.1109/ICICIP.2010.5565272","DOIUrl":null,"url":null,"abstract":"In this paper, a calibration method for platform inertial navigation system is proposed. By using this method, the calibration process can be completed without any turntables. For the inertial navigation platform which has full degrees of freedom in Yaw axis and ±60° degrees of freedom in the Roll and Pitch axis, a four-position field calibration method using receding horizon Kalman filter (RHKF) is proposed; scale factors and drifts of two horizontal gyros are estimated; based on local gravitational acceleration, scale factors and biases of accelerometers are also estimated. Simulation results show that compared with the traditional Kalman filter method, the method based on RHKF guarantees the rapidity and accuracy of the calibration, which can be adopted in the engineering applications.","PeriodicalId":152024,"journal":{"name":"2010 International Conference on Intelligent Control and Information Processing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Field calibration for platform inertial navigation system based on RHKF\",\"authors\":\"Fan Mo, Z. Deng, Bo Wang, M. Fu\",\"doi\":\"10.1109/ICICIP.2010.5565272\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a calibration method for platform inertial navigation system is proposed. By using this method, the calibration process can be completed without any turntables. For the inertial navigation platform which has full degrees of freedom in Yaw axis and ±60° degrees of freedom in the Roll and Pitch axis, a four-position field calibration method using receding horizon Kalman filter (RHKF) is proposed; scale factors and drifts of two horizontal gyros are estimated; based on local gravitational acceleration, scale factors and biases of accelerometers are also estimated. Simulation results show that compared with the traditional Kalman filter method, the method based on RHKF guarantees the rapidity and accuracy of the calibration, which can be adopted in the engineering applications.\",\"PeriodicalId\":152024,\"journal\":{\"name\":\"2010 International Conference on Intelligent Control and Information Processing\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Intelligent Control and Information Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICIP.2010.5565272\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Intelligent Control and Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICIP.2010.5565272","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Field calibration for platform inertial navigation system based on RHKF
In this paper, a calibration method for platform inertial navigation system is proposed. By using this method, the calibration process can be completed without any turntables. For the inertial navigation platform which has full degrees of freedom in Yaw axis and ±60° degrees of freedom in the Roll and Pitch axis, a four-position field calibration method using receding horizon Kalman filter (RHKF) is proposed; scale factors and drifts of two horizontal gyros are estimated; based on local gravitational acceleration, scale factors and biases of accelerometers are also estimated. Simulation results show that compared with the traditional Kalman filter method, the method based on RHKF guarantees the rapidity and accuracy of the calibration, which can be adopted in the engineering applications.