Cooperative Threat Assessment of Multi-aircrafts Based on Synthetic Fuzzy Cognitive Map

Threat assessment is one of the most important parts of the tactical decisions,and it has a very important influence on task allocation.An application of fuzzy cognitive map(FCM) for target threat assessment in the air combat is introduced.Considering the fact that the aircrafts participated in the cooperation may not have the same threat assessment mechanism,two different FCM models are established.Using the method of combination,the model of cooperative threat assessment in air combat of multi-aircrafts is established.Simulation results show preliminarily that the method is reasonable and effective.Using FCM for threat assessment is feasible.

Mission decision-making method of multi-aircraft cooperatively attacking multi-target based on game theoretic framework

Coordinated mission decision-making is one of the core steps to effectively exploit the capabilities of cooperative attack of multiple aircrafts. However, the situational assessment is an essential base to realize the mission decision-making. Therefore, in this paper, we develop a mission decision-making method of multi-aircraft cooperatively attacking multi-target based on situational assessment. We have studied the situational assessment mathematical model based on the Dempster-Shafer(D-S) evidence theory and the mission decision-making mathematical model based on the game theory. The proposed mission decision-making method of antagonized airfight is validated by some simulation examples of a swarm of unmanned combat aerial vehicles(UCAVs)that carry out the mission of the suppressing of enemy air defenses(SEAD).

Study on the resolution of multi-aircraft flight conflicts based on an IDQN

With the rapid growth of flight flow,the workload of controllers is increasing daily,and handling flight conflicts is the main workload.Therefore,it is necessary to provide more efficient conflict resolution decision-making support for controllers.Due to the limitations of existing methods,they have not been widely used.In this paper,a Deep Reinforcement Learning(DRL)algorithm is proposed to resolve multi-aircraft flight conflict with high solving efficiency.First,the characteristics of multi-aircraft flight conflict problem are analyzed and the problem is modeled based on Markov decision process.Thus,the Independent Deep Q Network(IDQN)algorithm is used to solve the model.Simultaneously,a’downward-compatible’framework that supports dynamic expansion of the number of conflicting aircraft is designed.The model ultimately shows convergence through adequate training.Finally,the test conflict scenarios and indicators were used to verify the validity.In 700 scenarios,85.71%of conflicts were successfully resolved,and 71.51%of aircraft can reach destinations within 150 s around original arrival times.By contrast,conflict resolution algorithm based on DRL has great advantages in solution speed.The method proposed offers the possibility of decision-making support for controllers and reduce workload of controllers in future high-density airspace environment.

Modeling method for integration of air command and security process

Air command and security(ACS)process is a kind of typical complex operation process.Its modeling issue has become a hot spot and challenge in the research field of complex operation process.Combining the demand on the application of air command and support,this paper proposes a simulation-based modeling method of integrating air command and support process,emphatically describing such aspects as the meta-model of the concept of aviation support process,work flow service modeling and arrangement of multi-aircraft process,etc.Finally,based on actual cases of application,this paper unfolds simulating verification and assessment on the whole process of control and support operation process of a flight task involving multiple aircrafts.