Unmanned Aerial vehicle's runway landing system with efficient target detection by using morphological fusion for military surveillance system

摘要

In the surveillance of military system Unmanned Ariel vehicles (UAVs) offers a remarkable service. Software Defined Network (SDN) is one of approach for UAV for improving target localization with surveillance for many applications . One of the critical issues for an Unmanned Ariel vehicles (UAVs) landing is the detection of runway in a low visibility conditions with computer vision. Also, the key problem is the accurate and robust detection of runway. A method of runway detection for fixed wing UAVs with a forward-looking camera is uses sensor based communication in network framework between source (UAV'S) and destination (runway sensor). Yet, this depends on the technical experience for landing an UAV's safely. Nowadays, highly advanced equipments are being developed for improving safety and transportation system to handle the problem of landing under low visibility conditions. However, natural or habitual vision could be reduced during low visibility situations. This may be due to many meteorological factors like haze, darkness, fog etc. From the discussion made in this paper, the authors mainly concentrate on managing an aircraft system under low luminosity condition during the landing. In this research, effective Morphological fusion method is employed for the prediction of virtual runway imagery to avoid accident landing process. For this, fusion of sensor data for DEM (Digital Elevation Map) Data, infrared image (IR) and navigation parameter are used. The performance of this research using Morphological fusion method gives a fused image of the runway prediction for UAVs under poor visibility condition. After obtaining the fused image, it is involved in ROI (Region of Interest) contour tracing process to get the clear location of landing of an UAV's without harm. The virtual imaginary model can be produced through contour tracing to predict runway. By this method, a less prediction time or setting time is achieved and maximum accuracy is obtained through simulation using MATLAB tool. Finally, the proposed experimental outcomes are compared with the existing technology. The proposed approach will be use in aircraft sensor based communication between the network (source to destination) to detect the target and to provide a better surveillance for military applications.