导航

ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2020, Vol. 41 ›› Issue (7): 323692-323692.doi: 10.7527/S1000-6893.2020.23692

• Electronics and Electrical Engineering and Control • Previous Articles     Next Articles

Fast penetration path planning for stealth UAV based on improved A-Star algorithm

ZHANG Zhe1, WU Jian1,2, DAI Jiyang1, YING Jin1, HE Cheng1   

  1. 1. School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China;
    2. School of Reliability and System Engineering, Beihang University, Beijing 100083, China
  • Received:2019-11-29 Revised:2020-01-02 Online:2020-07-15 Published:2020-02-06
  • Supported by:
    National Natural Science Foundation of China (61663032); Aeronautical Science Foundation of China (2016ZC56003); Innovation Special Fund for Graduate of Nanchang Hangkong University (YC2019026)

Abstract: Aiming to solve the survival and penetration problems of the stealth Unmanned Aerial Vehicle (UAV) under high-definition netted radar defense systems in modern warfare, this paper proposes a stealth UAV theater penetration path planning technology based on an improved A-Star algorithm. Firstly, the penetration process of the stealth UAV is analyzed and modeled, and the kinematics model of the stealth UAV, the dynamic radar cross section characteristics and the calculation model of the netted radar detection probability are established. Then, in view of the shortcomings of traditional algorithms in solving the problem of stealth penetration and taking into full consideration of the requirements of rapidity and safety in the planned route, an improved A-Star algorithm is designed. The multi-layer variable step size search strategy and the attitude angle information of UAVs are introduced into the algorithm. Further combined with the rank K fusion criterion, this algorithm can judge the feasibility of the new track point by the detection probability of the netted radar system of the stealth UAV on each track. The simulation results show that the improved A-Star algorithm can quickly generate better penetration routes in the combat area under complex netted radar systems, exhibiting certain application value.

Key words: unmanned aerial vehicles, route planning, netted radar, A-Star algorithm, radar cross sections

CLC Number: