A Novel Real-Time Penetration Path Planning Algorithm for Stealth UAV in 3D Complex Dynamic Environment

计算机科学 渗透(战争) 运动规划 雷达 A*搜索算法 实时计算 模拟 路径(计算) 航空航天工程 算法 人工智能 工程类 运筹学 机器人 电信 程序设计语言
作者
Zhe Zhang,Jian Wu,Jiyang Dai,Cheng He
出处
期刊:IEEE Access [Institute of Electrical and Electronics Engineers]
卷期号:8: 122757-122771 被引量:85
标识
DOI:10.1109/access.2020.3007496
摘要

In recent years, stealth aircraft penetration path planning has been a significant research subject in the field of low altitude combat. However, previous works have mainly concentrated on the path planning for stealth unmanned aerial vehicle(UAV) in 2D static environment. In contrast, this paper addresses a novel real-time path planning algorithm for stealth UAV to realize the rapid penetration, which aims to devise a route penetration strategy based on the improved A-Star algorithm to address the problems of replanning for stealth UAV in 3D complex dynamic environment. The proposed method introduces the kinematic model of stealth UAV and detection performance of netted radar in the process of low altitude penetration. Additionally, POP-UP threats are adopted into three different threat scenarios, which is closer to the real combat environment. Moreover, further combined with the prediction technique and route planning algorithm, the multi-step search strategy is developed for stealth UAV to deal with POP-UP threats and complete the replanning of the route in different scenarios. Furthermore, the attitude angle information is integrated into the improved A-Star algorithm, which reflects the characteristics of the dynamic radar cross section(RCS) and conforms to the actual flight requirements for the stealth UAV. Finally, the improved A-Star algorithm, the sparse A-Star search (SAS), and the dynamic A-Star algorithm(D-Star) are respectively adopted to address the problem of penetration route planning for stealth UAV in three different threat scenarios. Numerical simulations are performed to illustrate that the proposed approach can achieve rapid penetration route planning for stealth UAV in a dynamic threat scenario, and verify the validity of the improved A-Star algorithm which is compared to the other two algorithms
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