  The application of cooperative localization in vehicular networks is
attractive to improve accuracy and coverage. Conventional distance measurements
between vehicles are limited by the need for synchronization and provide no
heading information of the vehicle. To address this, we present a cooperative
localization algorithm using posterior linearization belief propagation (PLBP)
utilizing angle-of-arrival (AoA)-only measurements. Simulation results show
that both directional and positional root mean squared error (RMSE) of vehicles
can be decreased significantly and converge to a low value in a few iterations.
Furthermore, the influence of parameters for the vehicular network, such as
vehicle density, communication radius, prior uncertainty and AoA measurements
noise, is analyzed.
