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A New Spacecraft Impact Damage Feature Extraction Algorithm Based on Dynamic Multi-Objective Optimization Method

For infrared thermal damage feature extraction of M/OD impact damages, the multi-objective optimization algorithm can be used to get more accurate extraction results. But the algorithm needs to take a lot of evolution time to calculate PF. For the purpose of increasing the effectiveness of algorithm, the paper proposes a new spacecraft impact damage feature extraction algorithm based on dynamic multi-objective optimization method. According to historical information about the environment, some initial points that are hoped to be similar to the true PS are predicted by our algorithm. The framework of our method is: Firstly, the description of the space distribution of PS in the prior environment is realized by description individuals (DIs). Secondly, the production of initial points in the current environment is realized along the predicted orientation, which is generated by DIs. Thirdly, the calculation of PF is finished by Chebyshev decomposition approach, and based on the PF, the required STCs is selected by fuzzy set theory. Finally, according to the selected STCs, the damage feature image can be finished. Experiments have been carried out to test and verify the effectiveness of the presented algorithm.