{"title":"采用具有最优重要函数的粒子过滤器进行室内定位","authors":"Leila Pishdad, F. Labeau","doi":"10.1109/WPNC.2012.6268742","DOIUrl":null,"url":null,"abstract":"Particle filters have been widely used in positioning problems, to post-process the noisy location sensor measurements. In this paper, instead of the commonly used Prior Importance Function for particle filtering, we have formulated and applied the Optimal Importance Function. Unlike other importance functions, the Optimal Importance Function minimizes the variance of particle weights and thus resolves the degeneracy problem of particle filters. In this work, we have derived a closed form formula for the Optimal Importance Function using map-independent random walk velocity motion model and a GMM sensor error. Due to the generality of the proposed method, it can be used for a wide range of moving objects in different environments. Simulation results support the validity of modeling assumptions and the advantage of applying an Optimal Importance Function in indoor localization and positioning.","PeriodicalId":399340,"journal":{"name":"2012 9th Workshop on Positioning, Navigation and Communication","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Indoor positioning using particle filters with optimal importance function\",\"authors\":\"Leila Pishdad, F. Labeau\",\"doi\":\"10.1109/WPNC.2012.6268742\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Particle filters have been widely used in positioning problems, to post-process the noisy location sensor measurements. In this paper, instead of the commonly used Prior Importance Function for particle filtering, we have formulated and applied the Optimal Importance Function. Unlike other importance functions, the Optimal Importance Function minimizes the variance of particle weights and thus resolves the degeneracy problem of particle filters. In this work, we have derived a closed form formula for the Optimal Importance Function using map-independent random walk velocity motion model and a GMM sensor error. Due to the generality of the proposed method, it can be used for a wide range of moving objects in different environments. Simulation results support the validity of modeling assumptions and the advantage of applying an Optimal Importance Function in indoor localization and positioning.\",\"PeriodicalId\":399340,\"journal\":{\"name\":\"2012 9th Workshop on Positioning, Navigation and Communication\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 9th Workshop on Positioning, Navigation and Communication\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WPNC.2012.6268742\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 9th Workshop on Positioning, Navigation and Communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WPNC.2012.6268742","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Indoor positioning using particle filters with optimal importance function
Particle filters have been widely used in positioning problems, to post-process the noisy location sensor measurements. In this paper, instead of the commonly used Prior Importance Function for particle filtering, we have formulated and applied the Optimal Importance Function. Unlike other importance functions, the Optimal Importance Function minimizes the variance of particle weights and thus resolves the degeneracy problem of particle filters. In this work, we have derived a closed form formula for the Optimal Importance Function using map-independent random walk velocity motion model and a GMM sensor error. Due to the generality of the proposed method, it can be used for a wide range of moving objects in different environments. Simulation results support the validity of modeling assumptions and the advantage of applying an Optimal Importance Function in indoor localization and positioning.