Journal of Systems Engineering and Electronics ›› 2013, Vol. 35 ›› Issue (1): 78-84.doi: 10.3969/j.issn.1001-506X.2013.01.13

• 系统工程 • 上一篇    下一篇

基于自适应伪谱法的UCAV低可探测攻击轨迹规划研究

刘鹤鸣,丁达理,黄长强,黄汉桥,王铀   

  1. 空军工程大学航空航天工程学院, 陕西 西安 710038
  • 出版日期:2013-01-23 发布日期:2010-01-03

UCAV low observable attacking trajectory planning based on adaptive pseudospectral method

LIU He-ming, DING Da-li, HUANG Chang-qiang, HUANG Han-qiao, WANG You   

  1. Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi’an 710038, China
  • Online:2013-01-23 Published:2010-01-03

摘要:

研究无人作战飞机(unmanned combat aerial vehicle,UCAV)对地攻击阶段轨迹规划问题。首先,在综合UCAV的气动力特性、发动机推力特性基础上建立UCAV质点模型和动力学模型,并结合UCAV平台初始条件、机动性以及武器投射条件构建约束条件;针对当前轨迹规划中没有考虑雷达散射截面(radar cross section,RCS)随UCAV姿态角改变而动态变化这一缺陷,建立综合考虑动态RCS的威胁概率和攻击时间的目标函数;然后利用可变低阶自适应伪谱法求得攻击轨迹最优解。对时间最短、RCS固定和考虑动态RCS 3种情况进行仿真。结果表明,考虑动态RCS时,UCAV将根据威胁进行轨迹和姿态调整,极大减小了被敌方威胁捕获的概率。该算法能够提供规划轨迹的高精度状态和控制量信息,有利于实现攻击过程的高精度精细规划控制。

Abstract:

The issue of generating optimal air-to-ground weapon delivery trajectory planning strategy for unmanned combat aerial vehicle (UCAV) is studied. First, high fidelity 3 degrees of freedom(3-DoF) model and dynamic model are built considering initial states constraints, kinematic and dynamic constraints and final states constraints for weapon delivery. Second, to improve the limitation of traditional path planning method which does not consider the dynamic variation of radar cross section (RCS) with attitude angle of UCAV, a dynamic RCS model is used in the threat probability model which combines with trajectory flying time forms the object function. A variable loworder adaptive pseudospectral method is used to get the optimal trajectory. Finally, numerical examples for a minimum timeconsumption trajectory, a static RCS trajectory as well as a dynamic RCS trajectory are used to demonstrate the merits of the dynamic RCS. The result shows that when considering the dynamic RCS, UCAV can change its trajectory and attitude according to the threat which greatly eliminates the probability of being detected. This trajectory planning strategy can greatly improve the precision of states and controls, and can be used for a delicate plan and control of the whole weapon delivery process.