Distributed Direct Localization Suitable for Dense Networks
Journal article, 2020
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.
network localization
Uncertainty
Complexity theory
Fisher information (FI)
Data mining
Gold
Estimation
distributed particle filter
direct position estimation (DPE)
Signal to noise ratio
Distance measurement
Author
Siwei Zhang
German Aerospace Center (DLR)
Emanuel Staudinger
German Aerospace Center (DLR)
Thomas Jost
German Aerospace Center (DLR)
Wei Wang
German Aerospace Center (DLR)
Christian Gentner
German Aerospace Center (DLR)
Armin Dammann
German Aerospace Center (DLR)
Henk Wymeersch
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Peter Adam Hoeher
University of Kiel
IEEE Transactions on Aerospace and Electronic Systems
0018-9251 (ISSN) 15579603 (eISSN)
Vol. 56 2 1209-1227 8762217Subject Categories
Control Engineering
Signal Processing
Other Electrical Engineering, Electronic Engineering, Information Engineering
DOI
10.1109/TAES.2019.2928606