Multisensor data fusion and decision support for airborne target identification

A knowledge-based approach and a reasoning system for multisensor data fusion is presented. The scenario taken for the example is an air-land battlefield situation. A data fusion system obtains data from a variety of sensors. A Dempster-Shafer approach to representing and combining data is found appropriate for combining uncertain information from these disparate sensor sources at different levels of abstraction. Evidential reasoning allows confidences to be assigned to sets of propositions rather than to just N mutually exclusive propositions. The software has been developed in the Lisp language and tested. The results illustrate the advantages of using multiple sensors in terms of increase in detection probability, increased spatial and temporal coverage, and increased reliability