Abstract:
We consider the spatial localization of nodes in a network, based on measurements of their relative position with respect to their neighbors. These measurements include t...Show MoreMetadata
Abstract:
We consider the spatial localization of nodes in a network, based on measurements of their relative position with respect to their neighbors. These measurements include the nodes' relative positions in a global coordinate system, their distances, or their pseudo ranges. We show that the maximum likelihood estimator associated with these localization problems can be viewed as a constrained optimization problem with a specific structure and provide a distributed algorithm to solve it. Under appropriate assumptions, it is shown that the maximum likelihood estimates are locally asymptotically stable equilibrium points of the proposed algorithm. As a case study, we consider a range-based localization problem and present simulation results to evaluate the algorithm.
Date of Conference: 12-15 December 2017
Date Added to IEEE Xplore: 22 January 2018
ISBN Information: