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Meyer, Florian; Hlinka, Ondrej; Wymeersch, Henk; Riegler, Erwin; Hlawatsch, Franz
IEEE transactions on signal and information processing over networks, 03/2016, Letnik: 2, Številka: 1Journal Article
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.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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