Abstract
This research focuses on trajectory generation algorithms that take into account the stealthiness of autonomous UAVs; generating stealthy paths through a region laden with enemy radars. The algorithm is employed to estimate the risk cost of the navigational space and generate an optimized path based on the user-specified threshold altitude value. Thus the generated path is represented with a set of low-radar risk waypoints being the coordinates of its control points. The radar-aware path planner is then approximated using cubic B-splines by considering the least radar risk to the destination. Simulated results are presented, illustrating the potential benefits of such algorithms.
Highlights
Unmanned aerial vehicles (UAVs) are increasingly being used in real-world applications [1,2,3]
This research focuses on trajectory generation algorithms that take into account the stealthiness of autonomous Unmanned Aerial Vehicles (UAVs); generating stealthy paths through a region laden with enemy radars
These aerial vehicles are usually mobilized to carry out critical missions in high-risk environments, in situations where it may be hazardous for human operators
Summary
Such as threats, evolving mission elements, tight timing and positioning requirements. The term flight envelope refers to the parameters within which an aerial vehicle may be safely flown under varying, though expected, wind speed, wing loading, wind shear, visibility and other flight conditions without resorting to extreme control measures such as abnormal spin, or stall recovery, or crash landing These aerial vehicles are usually mobilized to carry out critical missions in high-risk environments, in situations where it may be hazardous for human operators. It is important to test the adjacency of two cells to find a path crossing the portion of the boundary shared by the two cells Both exact cell decomposition and approximate cell decomposition methods are accurate, yet may be computationally expensive when used in a terrain environment since numerous obstacles at varying elevations could be found.
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