The Study on the Dynamic Multi-objective Recognition and Estimation Algorithm of Infrared Imaging Based on Particle Swarms Collaboration

Recently, a problem that the infrared decoy interferes infrared detection system, cannot be solved. With the gradual application and popularity of the particle swarm optimization, it is preferable to apply it to dynamic multiobjective optimization 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 is based on the multi-particle swarms collaboration, ultimately estimates the motion trajectory and Pareto optimal solution of the 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, which produces favorable optimized effects. The experiment has great engineering significance.