Decentralised multi-sensor target tracking with limited field of view via possibility theory
Jérémie Houssineau, Chenbao Xue, Han Cai, Murat Üney, Emmanuel Delande · 2024
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.