Collaborative Tracking And Scheduling Based On Airborne Multi-sensor System

With the development of science and technology,new changing and thinking is brought out for the modern battlefield system.Single sensor tracking cannot meet the operational needs anymore,in order to obtain the best effect of combat,multi-sensor cooperation is indispensable.In order to solve the problem of airborne multi-sensor collaborative tracking and intelligent scheduling,this paper makes some improvements on fusion-filtering system and intelligent scheduling scheme with actual environment and target properties taken into account.Firstly,considered the coordination of airborne radar and infrared sensor on target tracking problem.An algorithm of fusion filtering based on minimum root mean square error and interactive multiple model filtering using unscented Kalman filter is proposed.The simulation results shows that it has superior tracking precision over underclocking fusion and basic IMM filter in asynchronous nonlinear tracking fusion.Then,considered the multi-sensor management,this paper presents an algorithm of modified efficiency function which synthetically considers the environmental factors,mission requirements,target statements and sensor characteristics to make it self-adaptive and suitable for multi-sensor management in resource limited area.It could realize the self-adaptive scheduling on tracking accuracy under environmental and resource constraints.The simulation on PAR,IRST and ESM show that the algorithm is reasonable and effective.