This paper addresses the problem of 3-D location estimation from perturbed range information and uncertain anchor positions. The 3-D location estimation problem is formulated as a min-max convex optimization problem with a set of second-order cone constraints. Robust optimization tools are applied to convert these cone constrains to semi-definite programming constraints and achieve robust location estimation without prior knowledge of the statistical distributions of the errors. Simulation results demonstrate the superiority of the proposed approach over other benchmark algorithms in a wide range of measurement error scenarios.
|Original language||English (US)|
|Title of host publication||2018 15th Workshop on Positioning, Navigation and Communications (WPNC)|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|State||Published - Dec 4 2018|