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提出了一种针对发现新目标后,机上在线进行航迹点重规划的方法.建立了重规划数学模型,用图像质量方程预估侦察目标的图像质量,以所有目标图像质量的加权之和最大、路径长度最小为目标函数.在传感器侦察范围、飞机机动和目标图像质量要求以及威胁等多约束条件下运用改进后的多目标进化算法NSGA-II寻优,得到侦察航迹点的Pareto最优解集.以目标图像质量、路径长度和路径威胁为评价因素,专家系统给出当前评价因素加权权值,用模糊选优方法在Pareto最优解集中选择该加权意义下的唯一最优路径.仿真结果证明了该方法的可行性和智能性.
Aiming at the point-to-point re-planning of on-board flight track after finding new targets, a mathematic model of re-planning was established, the image quality equation was used to estimate the image quality of reconnaissance targets, and the weighted sum of all target images was the largest , The minimum path length is the objective function.Using the improved multi-objective evolutionary algorithm NSGA-II to optimize the Pareto optimality of the reconnaissance trackpoints under multiple constraints such as the reconnaissance range, aircraft maneuver and target image quality requirements and threats, Solution set.Using the target image quality, path length and path threat as the evaluation factors, the expert system gives the weighted value of the current evaluation factors and selects the only optimal path in the Pareto optimal solution set by fuzzy optimization method. Simulation results prove the feasibility and intelligence of this method.