Online penetration trajectory planning using blind areas of network radar system for an unmanned combat aerial vehicle
Aircraft Engineering and Aerospace Technology
ISSN: 0002-2667
Article publication date: 18 November 2024
Issue publication date: 21 November 2024
Abstract
Purpose
A densely distributed network radar system compensates for the disadvantages of sparse radars and poses a significant threat to low-altitude penetration by an unmanned combat aerial vehicle (UCAV). Unlike previous studies, this paper aims to consider radar blind areas and proposes a rapid online method for planning low-altitude penetration paths.
Design/methodology/approach
First, the optimization problem coupling digital elevation map (DEM), radar detection probability model and nonholonomic UCAV kinematic model is established. Second, an online solution framework of penetration path planning is constructed. An intervisibility method and map scaling are proposed to generate a detection probability map (DPM). Through completeness and consistency analysis, an adaptive hybrid A* algorithm with fast local replanning strategy is proposed to search a path that takes into account time-consuming, detection probability under nonholonomic constraints. Finally, three scenarios of multiple known, pop-up and vanished static radars are simulated using C++. The computational performance is compared and analyzed.
Findings
The results showed that the proposed online method can generate low-detection-probability penetration paths within subseconds.
Originality/value
This paper provides a new online method to plan UCAV penetration trajectory in military and academic contexts.
Keywords
Acknowledgements
Funding: This research is supported by the Postdoctoral Fellowship Program of CPSF under Grant Number GZC20233371.
Citation
Ge, J., Xiang, J. and Li, D. (2024), "Online penetration trajectory planning using blind areas of network radar system for an unmanned combat aerial vehicle", Aircraft Engineering and Aerospace Technology, Vol. 96 No. 10, pp. 1321-1328. https://doi.org/10.1108/AEAT-07-2024-0207
Publisher
:Emerald Publishing Limited
Copyright © 2024, Emerald Publishing Limited