Method for reconstructing the directional pattern of opportunistic array radar with dynamic elements

In order to solve the pattern synthesis problem of opportunity array radar, a dynamic array element pattern synthesis mathematical model and opportunity unit reconstruction scheme based on correlation chance programming under uncertain scenarios are established. The model is optimized to maximize the reliability of task requirements,and is solved by fuzzy simulation and mathematical analysis under given relevant constraints. In addition, a parallel differential evolution algorithm with secondary mutation(SMPDE) is proposed to improve the adaptability of opportunity array radar to different environments and tasks. By constructing Hanke matrices using different ideal radar arrays, feasible and base regions for initial population evolution can be obtained. On this basis, elements are added or deleted according to the requirements and new elements are flexibly arranged through differential evolution to obtain the best performance. In the process of iteration, the time point of secondary mutation is determined in real time according to the evolution curve and the potential inferior evolution is terminated in time. The simulation and analysis show that the model can achieve the maximum reliability of the task target in the current environment when the pattern reconstruction problem is involved, especially the opportunity array radar with multiple dynamic elements. Moreover, the model can flexibly reconstruct and optimize the pattern according to different requirements under different conditions to further enhance the overall robustness of the system.