Improving identification capability of UCAV (Unmanned Combating Air Vehicle)

Existing identification capability of UCAV, as occasionally found in the open literature, is, in our opinion, not satisfactory and can be much improved. We present a method that we think does much improve such capability. Our new method uses the discrete fuzzy dynamic Bayesian network as the tool of inference to determine the category of the target from just several observable parameters that characterize the target. Simulation results show preliminarily that; (1) our method can integrate various rather obscure target characteristics and make them conspicuous as a whole; (2) various characteristics reinforce and modify each other; (3) the values of the same characteristic at different instants reinforce and modify each other; (4) the above three achievements overcome the limitation unavoidable if identification relies on only a single characteristic (many existing identification methods just rely on a single characteristic).