Techniques in Kalman Filtering for Autonomous Vehicle Navigation

Simple item page
dc.contributor.authorJones, Philip Andrewen
dc.contributor.committeechairWicks, Alfred L.en
dc.contributor.committeememberBird, John P.en
dc.contributor.committeememberMeehan, Kathleenen
dc.contributor.departmentMechanical Engineeringen
dc.date.accessioned2017-06-13T19:44:09Zen
dc.date.adate2015-06-25en
dc.date.available2017-06-13T19:44:09Zen
dc.date.issued2015-05-05en
dc.date.rdate2015-06-25en
dc.date.sdate2015-05-19en
dc.description.abstractThis thesis examines the design and implementation of the navigation solution for an autonomous ground vehicle suited with global position system (GPS) receivers, an inertial measurement unit (IMU), and wheel speed sensors (WSS) using the framework of Kalman filtering (KF). To demonstrate the flexibility of the KF several methods are explored and implemented such as constraints, multi-rate data, and cascading filters to augment the measurement matrix of a main filter. GPS and IMU navigation are discussed, along with common errors and disadvantages of each type of navigation system. It is shown that the coupling of sensors, constraints, and self-alignment techniques provide an accurate solution to the navigation problem for an autonomous vehicle. Filter divergence is discussed during times when the states are unobservable. Post processed data is analyzed to demonstrate performance under several test cases, such as GPS outage, and the effect that the initial calibration and alignment has on the accuracy of the solution.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-05192015-184107en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-05192015-184107/en
dc.identifier.urihttp://hdl.handle.net/10919/78128en
dc.language.isoen_USen
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectKalman Filteren
dc.subjectExtended Kalman Filteren
dc.subjectNavigationen
dc.subjectIMUen
dc.subjectGPSen
dc.titleTechniques in Kalman Filtering for Autonomous Vehicle Navigationen
dc.typeThesisen
dc.type.dcmitypeTexten
thesis.degree.disciplineMechanical Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

Files

Original bundle
Now showing 1 - 2 of 2
Thumbnail Image
Name:
etd-05192015-184107_Jones_PA_T_2015.pdf
Size:
2.68 MB
Format:
Adobe Portable Document Format
Download
Thumbnail Image
Name:
etd-05192015-184107_Jones_PA_T_2015_1.pdf
Size:
2.67 MB
Format:
Adobe Portable Document Format
Download

Collections

Masters Theses