@inproceedings{54a22b8f609448a99bdc61b1665e0646,
title = "Decentralised multi-sensor target tracking with limited field of view via possibility theory",
abstract = "Quantifying negative information in an efficient way is a challenging task, especially when this information has to be communicated on a network. In this article we leverage the unique properties offered by possibility theory to quantify and approximate the negative information arising in the context of tracking a target with a sensor that has a limited field of view. We also verify experimentally that the corresponding target tracking methodology can be applied in a decentralised manner to a sensor network, while maintaining a performance close to the idealised case where the initial location of the target is better-known.",
keywords = "Bernoulli filter, information fusion, inverted Gaussian mixture, negative information, Uncertainty modelling",
author = "Jeremie Houssineau and Chenbao Xue and Han Cai and Murat Uney and Emmanuel Delande",
note = "Publisher Copyright: {\textcopyright} 2024 ISIF.; 27th International Conference on Information Fusion, FUSION 2024 ; Conference date: 07-07-2024 Through 11-07-2024",
year = "2024",
doi = "10.23919/FUSION59988.2024.10706352",
language = "English",
series = "FUSION 2024 - 27th International Conference on Information Fusion",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "FUSION 2024 - 27th International Conference on Information Fusion",
address = "United States",
}