系统工程与电子技术 ›› 2019, Vol. 41 ›› Issue (4): 835-842.doi: 10.3969/j.issn.1001-506X.2019.04.19

• 系统工程 • 上一篇    下一篇

远距离支援最优干扰空域规划

王晴昊1, 姚登凯1, 胡剑波2, 赵顾颢1, 李宁3   

  1. 1. 空军工程大学空管领航学院, 陕西 西安 710051; 2. 空军工程大学装备管理与无人机工程学院,陕西 西安 710051;  3. 中国人民解放军94587部队, 江苏 连云港 222300
  • 出版日期:2019-03-20 发布日期:2019-03-20

Optimal airspace planning for sand off jamming

WANG Qinghao1, YAO Dengkai1, HU Jianbo2, ZHAO Guhao1, LI Ning3   

  1. 1. Air Traffic Control and Navigation College, Air Force Engineering University, Xi’an 710051, China;
    2. Material Management and UAV Engineering College, Air Force Engineering University, Xi’an 710051, China;
    3. Unit 94587 of the PLA, Lianyungang 222300, China
  • Online:2019-03-20 Published:2019-03-20

摘要:

针对支援突防作战中远距离支援干扰机最优空域的规划问题,确定了干扰机的配置范围、雷达探测范围,提出了航线安全间隔和有效干扰航段的概念,以有效干扰航段、干扰机数量和干扰机离雷达中心的距离三个参数构建评价函数,建立了远距离支援有源干扰空域规划的模型。该模型具有多约束、非线性的特点,因此采取灰狼优化算法对其求解,为降低在模型求解时算法陷入局部最优的概率,引入非线性调节参数和记忆功能对灰狼优化算法进行改进,继而规划出相应的空域。采用仿真的方式验证模型的合理性和求解算法的有效性,得到了不同决策偏好下的空域。

Abstract:

Aiming at planning of the optimal airspace of the stand off jammer in support penetration operations, the range of the jammer and the detection range of the radar after jamming are determined, the concepts of the standoff active jamming strategy, the route safety interval and the effective jamming segment are introduced and the calculation formulas are given. The evaluation function is constructed based on three parameters the effective jamming segment, the number of jammers and the distance of the jammer from the radar center. The model of the standoff active jamming airspace planning is established. The model is characterized, and the grey wolf optimization algorithm is used to solve it. In order to reduce the probability of falling into local optimum of the algorithm when solving the model, the nonlinear adjustment parameters and the memory function are utilized to improve the grey wolf optimization algorithm, and then the corresponding optimal airspace is planned. Simulations are carried out to verify the rationality of the model and the effectiveness of the algorithm, and the airspaces under different decision preferences are achieved.