Abstract:
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In this letter, we obtain the Maximum Likelihood
Estimator of position in the framework of Global Navigation
Satellite Systems. This theoretical result is the basis of a completely
different approach to the positioning problem, in contrast
to the conventional two-steps position estimation, consisting
of estimating the synchronization parameters of the in-view
satellites and then performing a position estimation with that
information. To the authors’ knowledge, this is a novel approach
which copes with signal fading and it mitigates multipath and
jamming interferences. Besides, the concept of Position–based
Synchronization is introduced, which states that synchronization
parameters can be recovered from a user position estimation. We
provide computer simulation results showing the robustness of
the proposed approach in fading multipath channels. The Root
Mean Square Error performance of the proposed algorithm is
compared to those achieved with state-of-the-art synchronization
techniques. A Sequential Monte–Carlo based method is used to
deal with the multivariate optimization problem resulting from
the ML solution in an iterative way. |