We propose a Bayesian method for distributed sequential localization of mobile networks composed of both cooperative agents and noncooperative objects. Our method provides a consistent combination of cooperative self-localization (CS) and distributed tracking (DT). Multiple mobile agents and objects are localized and tracked using measurements between agents and objects and between agents. For a distributed operation and low complexity, we combine particle-based belief propagation with a consensus or gossip scheme. High localization accuracy is achieved through a probabilistic information transfer between the CS and DT parts of the underlying factor graph. Simulation results demonstrate significant improvements in both agent self-localization and object localization performance compared to separate CS and DT, and very good scaling properties with respect to the numbers of agents and objects.
@article{arxiv.1403.1824,
title = {Distributed Localization and Tracking of Mobile Networks Including Noncooperative Objects - Extended Version},
author = {Florian Meyer and Ondrej Hlinka and Henk Wymeersch and Erwin Riegler and Franz Hlawatsch},
journal= {arXiv preprint arXiv:1403.1824},
year = {2016}
}