{"title":"基于嵌入式低成本免疫系统的室内PDR方法","authors":"Ling-feng Shi, Yaxuan Dong, Yifan Shi","doi":"10.1109/ICNSC55942.2022.10004055","DOIUrl":null,"url":null,"abstract":"Indoor Pedestrian Dead Reckoning (PDR) based on Inertial and Magnetic Measurement Unit (IMMU) can accurately provide the position of pedestrians, and gradually becomes popular research on indoor positioning. In this paper, a novel PDR algorithm based on low-cost IMMU is proposed, which implements PDR from four steps: step detection, gait detection, step size estimation and attitude solution. According to the pitch angle, it is judged whether a new step is generated, and gait detection algorithm based on the standard deviation of the acceleration modulus and the angular velocity threshold + the angular velocity standard deviation threshold is proposed, which is the basis of step length estimation and attitude solution. The performance of the algorithm is verified through indoor experiments. The results show that the average distance error in the indoor environment was 1.32% and the average end-to-end error was 1.21%. Therefore, this paper based on low-cost IMMU indoor PDR has great application value.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Indoor PDR Method Based on Foot-Mounted Low-Cost IMMU\",\"authors\":\"Ling-feng Shi, Yaxuan Dong, Yifan Shi\",\"doi\":\"10.1109/ICNSC55942.2022.10004055\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Indoor Pedestrian Dead Reckoning (PDR) based on Inertial and Magnetic Measurement Unit (IMMU) can accurately provide the position of pedestrians, and gradually becomes popular research on indoor positioning. In this paper, a novel PDR algorithm based on low-cost IMMU is proposed, which implements PDR from four steps: step detection, gait detection, step size estimation and attitude solution. According to the pitch angle, it is judged whether a new step is generated, and gait detection algorithm based on the standard deviation of the acceleration modulus and the angular velocity threshold + the angular velocity standard deviation threshold is proposed, which is the basis of step length estimation and attitude solution. The performance of the algorithm is verified through indoor experiments. The results show that the average distance error in the indoor environment was 1.32% and the average end-to-end error was 1.21%. Therefore, this paper based on low-cost IMMU indoor PDR has great application value.\",\"PeriodicalId\":230499,\"journal\":{\"name\":\"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)\",\"volume\":\"110 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNSC55942.2022.10004055\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNSC55942.2022.10004055","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Indoor PDR Method Based on Foot-Mounted Low-Cost IMMU
Indoor Pedestrian Dead Reckoning (PDR) based on Inertial and Magnetic Measurement Unit (IMMU) can accurately provide the position of pedestrians, and gradually becomes popular research on indoor positioning. In this paper, a novel PDR algorithm based on low-cost IMMU is proposed, which implements PDR from four steps: step detection, gait detection, step size estimation and attitude solution. According to the pitch angle, it is judged whether a new step is generated, and gait detection algorithm based on the standard deviation of the acceleration modulus and the angular velocity threshold + the angular velocity standard deviation threshold is proposed, which is the basis of step length estimation and attitude solution. The performance of the algorithm is verified through indoor experiments. The results show that the average distance error in the indoor environment was 1.32% and the average end-to-end error was 1.21%. Therefore, this paper based on low-cost IMMU indoor PDR has great application value.