Distributed Finite-Time Cooperative Localization for Three-Dimensional Sensor Networks

TL;DR

This paper presents a novel distributed finite-time localization algorithm for 3D sensor networks, combining barycentric coordinates, sum consensus, and conjugate gradient methods, with proven convergence and improved efficiency.

Contribution

It introduces a new theoretical condition for node localizability and develops a distributed finite-time localization algorithm with performance guarantees.

Findings

Algorithm achieves finite-time convergence to exact positions.

Numerical simulations show improved efficiency over existing methods.

Theoretical analysis guarantees localizability and convergence.

Abstract

This paper addresses the distributed localization problem for a network of sensors placed in a three-dimensional space, in which sensors are able to perform range measurements, i.e., measure the relative distance between them, and exchange information on a network structure. First, we derive a necessary and sufficient condition for node localizability using barycentric coordinates. Then, building on this theoretical result, we design a distributed localizability verification algorithm, in which we propose and employ a novel distributed finite-time algorithm for sum consensus. Finally, we develop a distributed localization algorithm based on conjugate gradient method, and we derive a theoretical guarantee on its performance, which ensures finite-time convergence to the exact position for all localizable nodes. The efficiency of our algorithm compared to the existing ones from the state-of-the-art literature is further demonstrated through numerical simulations.