Terminal Guidance of Unmanned Aerial Vehicle Based on Visual Information

The guidance system performance is critical particularly, during the terminal phase as the fast response and high accuracy are the leading parameters. The aided navigation based on optical flow (OF) is mainly used to enhance the gimbaled-seeker accuracy during the terminal phase of unmanned aerial vehicles to precisely find its targets without sharing the problem of long execution time which leads to degrade the vision system overall performance. In this paper, the visual information is mapped and translated to the proportional navigation guidance law (PNG) to define target dynamics to help unmanned aerial vehicles accurately detect and chase their targets. Statistical simulation is accomplished to examine the influence of large displacements on optical flow algorithms. The visual information obtained by the optical flow technique is filtered and smoothed before being translated to the guidance process. The simulation is carried out on an unmanned vehicle model for verification and validation of the effect of visual information for minimizing the miss-distance. The visual information can successfully minimize miss-distance under certain conditions with lower computations and faster processing time making it appropriate for terminal guidance of unmanned aerial vehicles.