Distributed Direct Localization Suitable for Dense Networks
Journal article, 2019

Traditional network localization algorithms contain ranging and localization steps, which have systematic disadvantages. We propose an algorithm dubbed direct particle filter based distributed network localization (DiPNet). A node's location is directly estimated from the received signals, incorporating location uncertainty of neighboring nodes. The propagation effects on DiPNet become insignificant for dense networks, due to the massive-link collective physical layer processing. DiPNet achieves a near-optimal performance with low complexity, which is particularly attractive for realtime dense-network localization.

Signal to noise ratio

Complexity theory

Data mining

Fisher information (FI)

Gold

Uncertainty

distributed particle filter

Estimation

direct position estimation (DPE)

network localization

Distance measurement

Author

Siwei Zhang

Emanuel Staudinger

Thomas Jost

Wei Wang

Christian Gentner

Armin Dammann

Henk Wymeersch

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

Peter Adam Hoeher

IEEE Transactions on Aerospace and Electronic Systems

0018-9251 (ISSN)

Subject Categories

Control Engineering

Signal Processing

Other Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1109/TAES.2019.2928606

More information

Latest update

9/16/2019