Piovan, GiuliaShames, ImanFidan, BarisBullo, FrancescoAnderson, Brian2015-12-13December 99781424431243http://hdl.handle.net/1885/84504We develop a novel localization theory for planar networks of nodes that measure each other's relative position, i.e., we assume that nodes do not have the ability to perform measurements expressed in a common reference frame. We begin with some basic definitions of frame localizability and orientation localizability. Based on some key kinematic relationships, we characterize orientation localizability for networks with angle-of-arrival sensing. We then address the orientation localization problem in the presence of noisy measurements. Our first algorithm computes a least-square estimate of the unknown node orientations in a ring network given angle-ofarrival sensing. For arbitrary connected graphs, our second algorithm exploits kinematic relationships among the orientation of node in loops in order to reduce the effect of noise. We establish the convergence of the algorithm, and through some simulations we show that the algorithm reduces the meansquare error due to the noisy measurements.Keywords: Angle of arrivals; Connected graphs; Least squares; Localizability; Localization problems; Localization theories; Mean-square errors; Noisy measurements; Planar networks; Reference frames; Relative positions; Ring networks; Sensing networks; Algorithms; K200810.1109/CDC.2008.47388092016-02-24