{"title":"Navigation Error Analysis in the ZUPT‐Aided Pedestrian Inertial Navigation","authors":"A. Shkel, Yusheng Wang","doi":"10.1002/9781119699910.ch6","DOIUrl":null,"url":null,"abstract":"This chapter analyzes navigation errors in Zero‐Velocity Update (ZUPT)‐aided pedestrian inertial navigation due to Inertial Measurement Unit (IMU) noises. It presents a 2D biomechanical model to simulate human gait to better understand human walking dynamics and also to serve as the basis for the following numerical simulations. Human ambulatory gait models are multidimensional due to the complex kinematic and dynamic relations between many parts of human body involved during walking. The foot motion can be superimposed on top of the torso motion to obtain the foot motion in the navigation frame. The navigation errors in the ZUPT‐aided navigation algorithm come mainly from two major sources: systematic modeling errors and IMU noises. The chapter presents verification of the analysis both numerically and experimentally. ZUPT‐aided inertial navigation algorithm eliminates the velocity drift during pedestrian navigation, and therefore greatly reduces the overall navigation error compared to the navigation result without any aiding.","PeriodicalId":371531,"journal":{"name":"Pedestrian Inertial Navigation with Self‐Contained Aiding","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pedestrian Inertial Navigation with Self‐Contained Aiding","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/9781119699910.ch6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This chapter analyzes navigation errors in Zero‐Velocity Update (ZUPT)‐aided pedestrian inertial navigation due to Inertial Measurement Unit (IMU) noises. It presents a 2D biomechanical model to simulate human gait to better understand human walking dynamics and also to serve as the basis for the following numerical simulations. Human ambulatory gait models are multidimensional due to the complex kinematic and dynamic relations between many parts of human body involved during walking. The foot motion can be superimposed on top of the torso motion to obtain the foot motion in the navigation frame. The navigation errors in the ZUPT‐aided navigation algorithm come mainly from two major sources: systematic modeling errors and IMU noises. The chapter presents verification of the analysis both numerically and experimentally. ZUPT‐aided inertial navigation algorithm eliminates the velocity drift during pedestrian navigation, and therefore greatly reduces the overall navigation error compared to the navigation result without any aiding.