Threat assessment of manned/unmanned combat aerial vehicle formation air-to-ground attack based on FBNs

During the process of air-to-ground attack under information environment, the threat information of ground entities is of high uncertainty. How to model the threat assessment of ground entities to aerial formation with an efficient uncertainty information inference method is a key issue demanding prompt solution. A threat assessment method of manned/unmanned aerial vehicle formation air-to-ground attack based on fuzzy Bayesian networks (FBNs) is proposed. This method integrates the advantages of fuzzy logic and Bayesian networks and can dispose the stochastic and fuzzy threat information. Simulation results indicate that FBNs can integrate not only the uncertainty information but also the subjective judgment of commanders, and fits the need of threat assessment inference in the uncertain combat environment.