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Data fusion system design and adaptive control

This paper addresses performance issues related to experimental validation data fusion systems. The paper considers the question of performance improvement as result of multisensor data fusion. More specifically, it addresses the question of whether it is feasible to design a fusion system so as to guarantee performance improvement beyond what is feasible by processing data from any single sensor only. Two theorems that provide an answer to the question and conditions under which such an improvement is feasible for centralized and distributed fusion are provided. Based on these two theorems, an optimal fusion architecture is discussed for predetection fusion. Shortcomings in applying the optimal fusion rules in the presence of partial statistical knowledge and means to overcome them are discussed. The need of data validation and adaptive sensitivity control in the fusion design, when optimality conditions are not satisfied, is demonstrated and suggestions for designing the feedback loop are given.