Node Localization Based on Distributed Constrained Optimization using Jacobi's Method [Conference Paper]

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.

External paper URL

Publication Forum: Proceedings of the 56th IEEE Conference on Decision and Control

Date: 2017-12-12

Place: Melbourne, Australia

Publisher: IEEE

Public Document?: Yes

NESL Document?: Yes

Document category: Conference Paper

Primary Research Area: Sensor and Actuator Networks