{"title":"组合导航滤波结果有效性在线评价及参数可用性研究","authors":"X. Bo, Bai Jing, Zang Junbo","doi":"10.1109/ICMA57826.2023.10215775","DOIUrl":null,"url":null,"abstract":"In recent years, the theory and methodology of integrated navigation system comprehensive evaluation have attracted much attention. Most of the existing parameter estimation methods are limited by the unknown prior information, and the integrated navigation state evaluation method also needs to evaluate the performance based on the external higher precision measurements. For integrated navigation, there are few studies on the effectiveness evaluation of filtering methods from the perspective of filtering process. This paper constructs an evaluation model of integrated navigation filtering algorithm, which combines projection pursuit technology. The best projection direction in projection pursuit technology is used to derive the weight of each filter performance index. In this paper, accelerated genetic algorithm is used to calculate the best projection direction. Finally, simulation experiments are carried out to simulate various navigation state simulation conditions, and the conventional Kalman filter and adaptive filter are compared. The conclusion of the simulation is that this method can be applied to the performance evaluation of the integrated navigation system fusion algorithm on the filtering mode.","PeriodicalId":151364,"journal":{"name":"2023 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Online Evaluation Of The Effectiveness Of Combined Navigation Filtering Results And Study Of Parameter Availability\",\"authors\":\"X. Bo, Bai Jing, Zang Junbo\",\"doi\":\"10.1109/ICMA57826.2023.10215775\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, the theory and methodology of integrated navigation system comprehensive evaluation have attracted much attention. Most of the existing parameter estimation methods are limited by the unknown prior information, and the integrated navigation state evaluation method also needs to evaluate the performance based on the external higher precision measurements. For integrated navigation, there are few studies on the effectiveness evaluation of filtering methods from the perspective of filtering process. This paper constructs an evaluation model of integrated navigation filtering algorithm, which combines projection pursuit technology. The best projection direction in projection pursuit technology is used to derive the weight of each filter performance index. In this paper, accelerated genetic algorithm is used to calculate the best projection direction. Finally, simulation experiments are carried out to simulate various navigation state simulation conditions, and the conventional Kalman filter and adaptive filter are compared. The conclusion of the simulation is that this method can be applied to the performance evaluation of the integrated navigation system fusion algorithm on the filtering mode.\",\"PeriodicalId\":151364,\"journal\":{\"name\":\"2023 IEEE International Conference on Mechatronics and Automation (ICMA)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE International Conference on Mechatronics and Automation (ICMA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMA57826.2023.10215775\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Mechatronics and Automation (ICMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA57826.2023.10215775","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Online Evaluation Of The Effectiveness Of Combined Navigation Filtering Results And Study Of Parameter Availability
In recent years, the theory and methodology of integrated navigation system comprehensive evaluation have attracted much attention. Most of the existing parameter estimation methods are limited by the unknown prior information, and the integrated navigation state evaluation method also needs to evaluate the performance based on the external higher precision measurements. For integrated navigation, there are few studies on the effectiveness evaluation of filtering methods from the perspective of filtering process. This paper constructs an evaluation model of integrated navigation filtering algorithm, which combines projection pursuit technology. The best projection direction in projection pursuit technology is used to derive the weight of each filter performance index. In this paper, accelerated genetic algorithm is used to calculate the best projection direction. Finally, simulation experiments are carried out to simulate various navigation state simulation conditions, and the conventional Kalman filter and adaptive filter are compared. The conclusion of the simulation is that this method can be applied to the performance evaluation of the integrated navigation system fusion algorithm on the filtering mode.