Recently, a problem that the infrared decoy interferes infrared detection system, cannot be solved. With thegradual application and popularity of the particle swarm optimization, it is preferable to apply it to dynamic multiobjectiveoptimization to solve the problem of the recognition and the estimation of dynamic multi-object in infrared imaging.In this study, the dynamic multi-objective estimation and recognition algorithm of the infrared imaging, which isbased on the multi-particle swarms collaboration, ultimately estimates the motion trajectory and Pareto optimal solution ofthe infrared imaging through the continuous improvement and upgradation of the particle swarms optimized algorithm,the continuous study and inheritance as well as the combination with the aerodynamic characteristic of the infrared decoy.The experiment proves that the improvement of particle swarm algorithm efficiently reduces the estimation error, whichproduces favorable optimized effects. The experiment has great engineering significance.
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