On the Equivalence Classes of Fusion Rules for Distributed Multisensor Decision Systems
分布式多传感器决策系统融合律的等价类(英文)

Under the assumption that the optimal sensor rules can be found for any given fusion rule, we analyze the conditions resulting in the performance equivalence and superiority between fusion rules for general distributed multisensor decision systems. To obtain globally optimal performance of a system, by applying the above results, we can partition all possible fusion rules into equivalence classes of fusion rules and compare performances between some of the equivalence classes; therefore, the number of the valuable fusion rules will be reduced greatly. Moreover,the above analysis does not depend on the statistical properties of the observation data as well as the objective of optimizing a certain system performance.