The main problem of ballistic missile early warning by the antimissile early warning radar network system is the duplicating of searching and tracking of multiple warheads with focused firing ballistic missiles. Then the detecting resource is close to saturation, and the whole warheads can't be tracked effectively. The model of coordination searching and tracking of antimissile early warning radar network system based on the genetic algorithm was proposed. The detection efficiency of radar network system was set as the objective function. The multiple warheads was distributed based on the genetic algorithm in view of the threat level of different warheads, the detection efficiency and the detection resource consumed of radars. The detection efficiency of radar was improved in the focused firing ballistic missiles scene. The model was established based on the STK software, and the correction of the algorithm was verified. The result is has important reference value to increasing the detection efficiency of the antimissile early warning radar network system.
The method of radar anti-jamming is by switching different measures by radar manipulator based on his experience currently, without considering the coordination of radar system. It will not be adapted for the requirement of anti-missile early warning within narrow time window in future. The model of optimization of coordinated anti-jamming was established based on the intelligent optimization algorithm. The genetic algorithm and the particle swarm optimization were compared and improved. The coefficient of radar importance, the value of benefit and cost of different antijamming measures were proposed. The probability of detection was used for estimating the effect of anti-jamming of netted radar system. The outcome of researching provides a useful reference for solving the problem of intelligent optimization of coordinated anti-jamming measures of anti-missile early warning in future.
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