NESL Technical Report #: 2017-12-3
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 proposed algorithm.
Publication Forum: Proceedings of the 56th IEEE Conference on Decision and Control
Place: Melbourne, Australia
Public Document?: Yes
NESL Document?: Yes
Document category: Conference Paper
Primary Research Area: #<ResearchArea:0x007f72f4ac8230>