  The initialization of the state estimation in a localization scenario based
on ranging and dead reckoning is studied. Specifically, we start with a
cooperative localization setup and consider the problem of recursively arriving
at a uni-modal state estimate with sufficiently low covariance such that
covariance based filters can be used to estimate an agent's state subsequently.
A number of simplifications/assumptions are made such that the estimation
problem can be seen as that of estimating the initial agent state given a
deterministic surrounding and dead reckoning. This problem is solved by means
of a particle filter and it is described how continual states and covariance
estimates are derived from the solution. Finally, simulations are used to
illustrate the characteristics of the method and experimental data are briefly
presented.
