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dc.contributor.advisorLachapelle, Gérard
dc.contributor.advisorPetovello, Mark
dc.contributor.authorHe, Zhe
dc.date.accessioned2013-01-25T22:43:15Z
dc.date.available2013-06-15T07:01:46Z
dc.date.issued2013-01-25
dc.date.submitted2013en
dc.identifier.citationHe, Z. (2013). High-Sensitivity GNSS Doppler and Velocity Estimation for Indoor Navigation (Unpublished doctoral thesis). University of Calgary, Calgary, AB. doi:10.11575/PRISM/26368en_US
dc.identifier.urihttp://hdl.handle.net/11023/499
dc.description.abstractDoppler measurements in global navigation satellite system (GNSS) receivers are useful for various purposes since they not only convey velocity and attitude information, but also directly relate with carrier phase measurements. When it comes to poor signal conditions, conventional high sensitivity GNSS receivers usually extend integration time in order to maintain track of weak GNSS signals. However, due to low signal-to-noise ratio (SNR) and multipath effects, the navigation accuracy is still degraded in this case. Thus maintaining track of Doppler frequency with acceptable accuracy in challenged indoor environments is important and will be beneficial for both standalone and integrated solutions. This thesis investigates how to obtain more reliable and robust Doppler frequency and velocity estimates with GNSS signals for indoor navigation. Doppler errors due to indoor multipath and user dynamics are first investigated. Experimental results show that these errors are further affected by some multipath statistics such as averaged multipath angle of arrivals (AOAs). A directional signal/multipath model is thus developed to characterize such errors. To mitigate the adverse effects brought by multipath signals, a direct vector receiver with GLONASS capability is therefore proposed and developed. It is shown that when the user has partial visibility of line-of-sight (LOS) satellite signals, both the velocity and Doppler estimation accuracy is improved as compared to conventional high sensitivity receivers. Geometry dependent factors are defined and used to quantify such improvements. Finally, the benefits of using such Doppler measurements for consistent navigation are evaluated in two real indoor environments. Doppler measurements from both direct vector receiver and conventional high sensitivity receiver are tightly integrated with a PDR algorithm. Results show that in large open space indoor environments, the former integration strategy significantly improves the navigation accuracy. For office like indoor environments, improvements of the former integration strategy are not very apparent, but still outperform the conventional integration strategy. All these indicate that the quality of Doppler estimated by direct vector receiver is as good as or better than the conventional one for the indoor environments considered herein.en_US
dc.language.isoeng
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectEngineering
dc.subjectEngineering--Aerospace
dc.subjectEngineering--Electronics and Electrical
dc.subject.classificationhigh-sensitivity GNSSen_US
dc.subject.classificationDoppleren_US
dc.subject.classificationVelocityen_US
dc.subject.classificationIndoor Navigationen_US
dc.subject.classificationGPSen_US
dc.subject.classificationGLONASSen_US
dc.titleHigh-Sensitivity GNSS Doppler and Velocity Estimation for Indoor Navigation
dc.typedoctoral thesis
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/26368
thesis.degree.nameDoctor of Philosophy
thesis.degree.namePhD
thesis.degree.disciplineGeomatics Engineering
thesis.degree.grantorUniversity of Calgary
atmire.migration.oldid679
dc.publisher.placeCalgaryen
ucalgary.item.requestcopytrue


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