Decision fusion strategies in multisensor environments

Efficient decision fusion strategies for deriving optimal decisions in multisensor target recognition/tracking environments are analyzed. The problem is viewed as one of parallel fusion of the individual independent decisions with a recursive structure that permits enhancement of the reliability of the fused decision. Instead of a voting-based fusion approach, this recursive structure can be combined with any one of the other optimal fusion techniques as well. An analysis based on a simple voting or consistency-measure-dependent fusion scheme is presented to illustrate the recursive model and its benefits. >

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