无人侦察机的航迹重规划

Route Re-planning for Reconnaissance Unmanned Aerial Vehicles

用图像质量方程预测各个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和总路径长度最小为目标,在传感器观察范围、飞机机动和对目标图像质量要求以及威胁等多个约束条件下进行多目标寻优确定侦察航迹点,得到Pareto最优路径集。以目标总图像质量、总路径长度和路径总威胁为评价因素,专家系统综合当前机上资源、目标特性和威胁等级给出评价因素加权,用模糊选优方法通在Pareto最优路径集中选择加权意义下的唯一最优路径。

Firstly mathematics model for re-planning is built,which is a multi-objective optimization under multi-constraint.Advanced multi-objective evolutionary algorithm is adopted to find the Pareto non-dominant route set,aiming at maximizing weighted image quality of each target and minimizing route length under constraints.While image quality of each target is forecasted by general image quality equation and constraints are determined by field-of-regard of sensor,dynamic motion of the vehicle,image quality demand,safety distance etc.At last,fuzzy selection is applied to select the optimal route from the Pareto non-dominant route set refer to weights of weighted image quality,route length and risk given by expert system according to fuel,targets and threats.The simulated result showed the rationality of the method.