A new approach for credibilistic multi-sensor association
Dominique Gruyer, Morgan Mangeas · 2003
Often, when several information sources are available, data are heterogeneous and asynchronous. The combination of all these information sources remains as a difficult task which strongly depends on the representation of the used data. Consequently, it is imperative to choose a model of knowledge representation well adapted to each kind of information. When each source is perfectly represented and modelled, we need to know how to associate them the most faithful and the most reliable way. In this paper, we propose a new credibilistic approach for multi-sensors data association able to resolve the problems mentioned above. This association algorithm provides a reliable and robust representation of an environment by using all available information.