Penetration path planning of stealthy UAV based on improved sparse A-star algorithm
Zitang Zhang, Chunrui Tang, Yibing Li · 2020
In some certain specific scenarios, path planning for UAVs is a hot topic of current research. This paper takes the low-altitude flight path planning of UAV in a single radar detection range as the research background. In the conventional SAS algorithm, the search area is greatly reduced. However, in the process of node expansion, it can only expand in a fixed direction, which is not flexible and has a certain chance to miss the best node. To solve this problem, this paper proposes an improved directional SAS algorithm. The algorithm first expands the search area by taking the line between two adjacent path points as the angular bisector, using the smallest step length as the search radius and adds the UAV's attitude limit to the expanded node to reduce the search area. The simulation is carried out and the results show that SAS algorithm proposed in this paper has the following advantages compared with the conventional SAS algorithm: 1) shorter path length 2) less calculation time 3) lower exposure ratio and lower mean high detection probability Pm.