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    Browsing by Subject "Kalman Filter"

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      • Advanced Nonlinear Techniques for Low Cost Land Vehicle Navigation 

        Georgy, Jacques (2010-07-27)
        Present land vehicle positioning and navigation relies mostly on the Global Positioning System (GPS). However, in urban canyons, tunnels, and other GPS-denied environments, the GPS positioning solution may be interrupted ...
      • Improved Land Vehicle Navigation and GPS Integer Ambiguity Resolution Using Enhanced Reduced-IMU/GPS Integration 

        Karamat, Tashfeen (2014-06-24)
        Land vehicle navigation is primarily dependent upon the Global Positioning System (GPS) which provides accurate navigation in open sky. However, in urban and rural canyons GPS accuracy degrades considerably. To help GPS ...
      • Integrated Cooperative Localization in VANETs for GPS Denied Environments 

        Elazab, Mariam (2015-10-07)
        Accurate and ubiquitous localization is the driving force for location based services in Vehicular Ad-hoc NETworks (VANETs). In urban areas, Global Positioning System (GPS) and in-vehicle navigation sensors (e.g. odometers) ...
      • Navigation in Wheeled Mobile Robots Using Kalman Filter Augmented with Parallel Cascade Identification to Model Azimuth Error 

        Rahman, Atif (2013-06-13)
        Unmanned ground mobile robots are land-based robots which do not have a human passenger on board. They can be either autonomous, or controlled via telecommunication. For navigational purposes, GPS is often used. However, ...
      • New Algorithms in Rigid-Body Registration and Estimation of Registration Accuracy 

        Hedjazi Moghari, Mehdi (2008-09-28)
        Rigid-body registration is an important research area with major applications in computer-assisted and image-guided surgery. In these surgeries, often the relationship between the preoperative and intraoperative images ...
      • A New Approach in Survival Analysis with Longitudinal Covariates 

        Pavlov, Andrey (2010-04-27)
        In this study we look at the problem of analysing survival data in the presence of longitudinally collected covariates. New methodology for analysing such data has been developed through the use of hidden Markov modeling. ...

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