Research On Air Target Predication Technology Of Fighting Intention

The predication technology of fighting intention can accurately analyze the linkage relationship among the elements of battlefield situation,grasp the key battlefield situation,help the commander to analyze and make decisions,so that the confrontation between the two sides develops according to the track of our ideal battle situation,therefore,it is an important method of intelligent warfare to gain the combat opportunities and achieve quick victory.In this paper,the attack and defense confrontation in a complex environment is used as the combat environment,the intelligent algorithms such as game theory,cloud model and two-tuple linguistic are used as the warfare theory,and the realization of quick victory is used as the warfare drive,in this paper,the air target predication technology of fighting intention is divided into three modules: main attack direction prediction,combat effectiveness evaluation and trend prediction,the specific contents are as follows:(1)Aiming at the problem of main attack direction prediction of enemy attacking targets,a method of main attack direction prediction based on the game cloud model is proposed.Firstly,this method constructs an index system with the surrounding terrain condition,the firepower striking ability and the shape of the defending target as situation elements;Then the game theory is used to analyze the game between subjective and objective methods,so as to obtain the Nash Equilibrium of the index weight;Finally,the optimal combination weight is introduced into the cloud model,which accurately realizes main attack direction prediction of the enemy attacking targets,the accuracy of this method is verified by software simulation experiments and comparison with other methods.(2)Aiming at the problem of combat effectiveness evaluation of enemy attacking targets,a two-tuple linguistic cloud model for combat effectiveness evaluation of enemy attacking targets is proposed.Firstly,an index system with target analysis,attack cost and combat capability as the situation elements is constructed;Firstly,by improving the two-tuplelinguistic model,the index values which only contain physical information is transformed into the information-rich two-tuple linguistic evaluation values;Then the corresponding two-tuple linguistic cloud variables and the cloud weight are obtained by combining the cloud model;Finally,the aggregation cloud is generated by cloud aggregation operator to rank combat effectiveness evaluation values,and the simulation results show that the method has good robustness.(3)Aiming at the problem of trend prediction of enemy attacking targets,a dual linguistic information game linkage model for enemy trend prediction is proposed.Firstly,the two-dimension two-tuple linguistic information model is used as the carrier,introduces a distance function,and dynamically correlates the semantic evaluation values of various battlefield indicators,so that the dual linguistic information set can dynamically evolve with the change of the battlefield environment;Secondly,game theory is used to combine information game analysis between expert decision preference set and expert decision dependent set in a dual linguistic,and corresponding dynamic scoring function of enemy attacking targets is constructed,and realize the optimal decision-making of the trend prediction plan of enemy in a strong confrontation and multi-complex combat environment;Finally,through software simulation experiments,comparative analysis with other methods to verify that the method has strong adaptability and robustness.