Download Uncertainty Theories and Multisensor Data Fusion by Alain Appriou PDF

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  • April 20, 2017
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By Alain Appriou

Addressing contemporary demanding situations and advancements during this transforming into box, Multisensor facts Fusion Uncertainty Theory first discusses uncomplicated questions comparable to: Why and whilst is a number of sensor fusion helpful? How can the to be had measurements be characterised in any such case? what's the function and the specificity of data fusion processing in a number of sensor structures? contemplating the several uncertainty formalisms, a suite of coherent operators equivalent to different steps of a whole fusion technique is then built, with a purpose to meet the necessities pointed out within the first a part of the booklet.

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1. Peculiarities of the problem Data fusion actually covers a very broad range of problems, depending on the nature of the information being exploited and the goal of the procedure, as shown by the discussion presented in [BLO 01]. With regard to the information being exploited, four major categories can be distinguished, a priori: – The observations captured by the sensors. – The knowledge available in the form of databases, expert knowledge bases, information, intelligence, etc. – The preferences used in multi-criterion decisions, with multiple decision-makers, etc.

The advantage of this equivalence is, evidently, that it transforms sure but imprecise information (proven realization of a fuzzy set of values) into precise but uncertain information (possibility of occurrence of a specific value), and vice versa. This needs to be compared to what happens when we characterize a measuring error (imprecision of the evaluation) by a stochastic process of measurement noise. This brief overview reveals a very significant similarity between the probabilistic and possibilistic approaches.

Yet this can become particularly damaging when the operators and processing that we can implement prove sensitive to the choice of membership functions and especially to the position of their nonlinear elements. 3. Possibility theory Developed by Zadeh himself on the basis of his fuzzy sets theory, possibility theory is intended to deal with the uncertainty of events. Directly inspired by the formalism of fuzzy sets applied to processing of imprecision, it appears at first glance to be a direct competitor for probability theory in terms of processing uncertainty.

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