Mission
Information Fusion is a process of combining information
collected from various disparate sources (multiple different sensors,
data bases, knowledge bases, communication lines) into one coherent
structure that can be used by a computer system to make a decision
that leads to achieving the system's goal.
With the continuous progress in sensor and communications technologies
the amount of information that is provided to computer systems is
constantly increasing, overwhelming both the computer systems and
the human operators. In spite of a significant progress in research
on Information Fusion, there is still a lack of a theoretical framework
for integrating disparate sources of information, and especially
for developing (specifying, designing) such systems.
Our mission is to work towards a theoretical (formal)
Information Fusion Framework in which the development of an Information
Fusion System can be represented as an operation of combining theories
associated with sensors, information sources, domains, system performance
criteria, and the fusion process itself. The keystone of our approach
is the recognition of the fact that fusion is an operation on those
theories (information structures), rather than just on data items;
it is developing new structures from old known structures and data.
We use category theory as the theoretical framework
in which we represent, compose and transform information structures
containing all knowledge in all of the phases of the fusion system
development process. These structures are stored in reusable libraries
(specifications). The development of the system is a process of
refinement and transformation of system goals into a working system,
using category theory operators (morphisms). This process preserves
the system invariant expressed in terms of a performance criterion.
In this framework, the resulting system is provably correct, i.e.,
it will obey the performance criterion, if the assumptions considered
in the process are true.
Our goal is to establish a radically new approach
to information fusion, resulting into a new discipline  theory
of information fusion. The basics of the information fusion theory
developed in this project will establish solid grounds for further
development and will point to directions for the search to solutions
of fusion problems. Among others, we are working on:
 Foundations for incorporating performance
measures and measures of effectiveness (MOE) of fusion, using
all kinds of treatments of uncertainty
 Means for the rationalization of architectures
of fusion and flexible architectures for the adaptation to changing
system requirements
 Automatic tool support for designing Information
Fusion Systems
 Basic theories of abstracting qualitative
information from quantitative sensory data through the utilization
of category theory and wavelet transformations
