{"title":"大学生卡尔曼滤波教程","authors":"M. Rhudy, R. Salguero, Keaton Holappa","doi":"10.5121/IJCSES.2017.8101","DOIUrl":null,"url":null,"abstract":"This paper presents a tutorial on Kalman filtering that is designed for instruction to undergraduate students. The idea behind this work is that undergraduate students do not have much of the statistical and theoretical background necessary to fully understand the existing research papers and textbooks on this topic. Instead, this work offers an introductory experience for students which takes a more practical usage perspective on the topic, rather than the statistical derivation. Students reading this paper should be able to understand how to apply Kalman filtering tools to mathematical problems without requiring a deep theoretical understanding of statistical theory.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"203 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"63","resultStr":"{\"title\":\"A Kalman Filtering Tutorial for Undergraduate Students\",\"authors\":\"M. Rhudy, R. Salguero, Keaton Holappa\",\"doi\":\"10.5121/IJCSES.2017.8101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a tutorial on Kalman filtering that is designed for instruction to undergraduate students. The idea behind this work is that undergraduate students do not have much of the statistical and theoretical background necessary to fully understand the existing research papers and textbooks on this topic. Instead, this work offers an introductory experience for students which takes a more practical usage perspective on the topic, rather than the statistical derivation. Students reading this paper should be able to understand how to apply Kalman filtering tools to mathematical problems without requiring a deep theoretical understanding of statistical theory.\",\"PeriodicalId\":415526,\"journal\":{\"name\":\"International Journal of Computer Science & Engineering Survey\",\"volume\":\"203 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-02-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"63\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computer Science & Engineering Survey\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5121/IJCSES.2017.8101\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computer Science & Engineering Survey","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/IJCSES.2017.8101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Kalman Filtering Tutorial for Undergraduate Students
This paper presents a tutorial on Kalman filtering that is designed for instruction to undergraduate students. The idea behind this work is that undergraduate students do not have much of the statistical and theoretical background necessary to fully understand the existing research papers and textbooks on this topic. Instead, this work offers an introductory experience for students which takes a more practical usage perspective on the topic, rather than the statistical derivation. Students reading this paper should be able to understand how to apply Kalman filtering tools to mathematical problems without requiring a deep theoretical understanding of statistical theory.