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We consider the problem of state estimation for a dynamic system driven by unobserved, correlated inputs. We model these inputs via an uncertain set of temporally correlated dynamic models, where this uncertainty includes the number of modes, their associated statistics, and the rate of mode transitions. The dynamic system is formulated via two interacting graphs: a hidden Markov model (HMM) and a...
In the condition of sensor network (SN), to associate local tracks front multiple sensors is a complex task, due to the combination explosion caused by the increasing number of sensors and targets. A new graphical models-based technique for track association is proposed in this paper to deal with the problem. Firstly, by means of the sparse structure inherent in multisensor multitarget tracking scenario,...
The knowledge of the principles and goals under which an adversary organization operates is required to predict its future activities. To implement successful counter-actions, additional knowledge of the specifics of the organizational structures, such as command, communication, control, and information access networks, as well as responsibility distribution among members of the organization, is required...
The main challenge of future phased array multifunction radar will be to optimise the radar time budget to avoid deleterious overload effects. For this purpose, we propose a new technique for priority assignment of Search Domains. Then, we have developed new algorithms for most threatening trajectories computation based on Calculus of Variations approach developed for "shortest path computation"...
Most of studies in the field of information fusion focus on the production of high-level information from low-level data. The challenge is then to fuse this high-level information to produce a global and coherent information. Another approach consists in interpreting data as high-level information and fuse it at once. Our approach relies on the use of conceptual graphs model. The model is widely used...
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