Distributed Localization and Tracking of Mobile Networks Including   Noncooperative Objects - Extended Version
  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. 
Florian Meyer, Ondrej Hlinka, Henk Wymeersch, Erwin Riegler, and Franz   Hlawatsch
cs.IT cs.DC math.IT