Algorithm for waypoints re-planning of reconnaissance unmanned aerial vehicles
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摘要: 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.Abstract: An on-line waypoints re-planner was presented .It is capable of adjusting trajectory when some targets are detected. A mathematics model of multi-objective optimization under multi-constraint for re-planning was built. Advanced NSGA-II was adopted to find the Pareto non-dominant route set, aiming at maximizing weighted image quality of each target and minimizing route length under constraints. By using the general image quality equation(GIQE), image quality of each target was forecasted. Constraints were determined by field-of-regard(FOR) of sensor, dynamic motion of the vehicle, image quality demand, safety distance etc. Fuzzy selection was applied to select the optimal route from the Pareto non-dominant route set refer to current weights of weighted image quality, route length and risk given by expert system. The simulated result showed the rationality and intelligence of the method.
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