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. INDEX TERMS Stealth unmanned aerial vehicle, dynamic radar cross-section, netted radar, real-time path planning, A-Star algorithm.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.