A new unified description of multisource-heterogeneous information

The paper incorporates fuzzy logic methodologies into mulitsensor- multitarget system under the framework of random set theory, and presents the logical unified description of the unambiguous information (Data) and a type of the uncertain information (Ambiguous Evidence) so as to construct qualitative measurement models for Data and Ambiguous Evidence fusion. The procedure is as follows: firstly, strong random set and week random set are defined, based on which, the unified description of Data and Ambiguous Evidence is introduced; secondly, according to characters of ambiguous evidences, tow Bayesian-markov nonlinear measurement models for the Data and Ambiguous Evidence fusion are presented; thirdly using "the models-based signature-matching scheme", the operation of the statistics of ambiguous evidence defined as random sets can be simplified to that of the membership functions of relative point state variables.