Dirichlet Process Mixtures for Density Estimation in Dynamic Nonlinear Modeling: Application to GPS Positioning in Urban Canyons

@article{Rabaoui2012DirichletPM,
  title={Dirichlet Process Mixtures for Density Estimation in Dynamic Nonlinear Modeling: Application to GPS Positioning in Urban Canyons},
  author={Asma Rabaoui and Nicolas Viandier and Emmanuel Duflos and Juliette Marais and Philippe Vanheeghe},
  journal={IEEE Transactions on Signal Processing},
  year={2012},
  volume={60},
  pages={1638-1655}
}
In global positioning systems (GPS), classical localization algorithms assume, when the signal is received from the satellite in line-of-sight (LOS) environment, that the pseudorange error distribution is Gaussian. Such assumption is in some way very restrictive since a random error in the pseudorange measure with an unknown distribution form is always induced in constrained environments especially in urban canyons due to multipath/masking effects. In order to ensure high accuracy positioning… CONTINUE READING
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