Fusion in Signal Processing - Information Fusion in Signal and Image Processing - page 25

sequence to modify a sensor's state. In reference to the seconds-long human reaction
time, this is called a long loop, as opposed to an automated system response.
However, control distribution generates very stringent constraints on the manage-
ment of telecommunications. The communications network can be either partly or
fully connected. In [GRI 92], a study on propagation and fusion of estimates in the
nodes of a multi-sensor network was conducted under three constraints: there had to
be no unique fusion center, communications were imposed from one node to another
and nodes had no overall information regarding the network, they only knew the nodes
to which they were connected. The goal was to find the optimal estimate to propagate,
using all the available and useful information, while minimizing redundancy.
Another approach to communications management in multi-sensor systems in-
volves setting up intelligent resource allocation based on information theory. In a
decentralized system, the objective is to quickly find a receiver for whom the informa-
tion it receives will maximize the change in its entropy. An intelligent mechanism
is compared with the standard round-robin mechanism in a multi-sensor tracking
system [DEA 97b] by relying on the information filter, and on a multi-sensor iden-
tification system [DEA 97a, GRE 96] by using a decentralized Bayesian algorithm.
Results show that the average and maximum waiting periods for communications can
be reduced. In identification, the number of targets processed is greater because of
this algorithm. In tracking, the system made it possible to reduce communications,
while still obtaining more specifics about the target, and more significantly for targets
following a uniform straight line trajectory or performing major maneuvers.
2.3. Problems and specificities of fusion in signal processing
By stating the three main types of objectives, we have stumbled upon a certain
number of sub-problems specific to fusion in signal processing. We will now discuss
a few of these basic subjects to show how they can be handled and solved.
2.3.1. Dynamic control
The complexity of an actual application is reflected not only in the volume of data
involved, but also and most importantly in the variety of mechanisms that need to
be taken into account in order to obtain a feasible solution. Supervising the whole
system consists of providing a plan regarding the fusion strategy that needs to be
implemented. There are currently two levels that coexist.
The first level is to provide contextual combination mechanisms in order to be able
to take into account context changes defined on the overall supervisor's level. The
objective is to bring back down to the combination level itself dissymmetric weight-
ings involving different elements of information being combined. Because the system