@inproceedings{dlr86457,
  author = {Fabian de Ponte M\"{u}ller and Alexander Steingass and T Strang},
  title = {{Zero-Baseline Measurements for Relative Positioning in Vehicular Environments}},
  year = {2013},
  month = {Dec},
  abstract = {{Forward collision warning systems, lane change assistants or cooperative adaptive cruise control are examples of safety relevant applications that rely on accurate relative positioning between vehicles. Current solutions estimate the position of surrounding vehicles by measuring the distance with a RADAR sensor or a camera system. One promising approach to extend the perception range of these sensors is the exchange of GNSS raw data measured from a vehicle to a set of satellites by using a inter-vehicle communication link. The aim of this approach is to cancel correlated errors in both receivers and thus achieving a better relative position estimate. The present paper shows the potential of this differential approach by showing the results of a series of zero-baseline experiments conducted in a simulated environment. The impact of uncorrelated errors that are not canceled out by differentiation, such as noise and multipath, is analyzed in depth and verified by simulations. The results show that in clear sky conditions and in absence of multipath propagation, the baseline of a vehicle can be estimated using GNSS pseudorange double differences with less than one meter of error. Multipath might severely degrade this performance, even in the case of a zero-baseline experiment.}},
  address = {Munich, Germany},
  booktitle = {Sixth European Workshop on GNSS Signals and Signal Processing},
}