A New Method of 3D Low_Observable Trajectory Optimization in Presence of Multiple Radars

摘要：

In this paper, we focus on the new method of finding an optimal aircraft trajectory to minimize the probability of detection by opponent radar detection systems and the total flight time. Three dimension (3D) aircraft and detection model is established first And then, support vector regression (SVR) method, which obtains good generalization on a limited number of learning patterns, is considered to fit the disordered data of detection model. Both trajectory constraints and boundary conditions are attained with high accuracy using Gauss pseudospectral method (GPM). Simulation results demonstrate the feasibility of the proposed method in trajectories optimization in presence of multiple radars for both detectability and flight time.

关键词： component 3D trajectory optimization GPM SVR Low_Observable RCS

作者: Shaofei Chen Hongfu Liu Jing Chen

作者单位: College of Mechatronics Engineering and Automation National University of Defense Technology Changsha, China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Automation Engineering(ICCAE 2011)(2011年第三届IEEE计算机与自动化工程国际会议)

会议地点: 重庆

会议语种:英文

页码: 449-453

在线出版日期: 2011-01-21（万方平台首次上网日期，不代表论文的发表时间）