Date of Award
Thesis - Open Access
Master of Science in Electrical & Computer Engineering
Dr. Jianhua Liu
First Committee Member
Dr. Richard Prazenica
Second Committee Member
Dr. Ilteris Demirkiran
For unmanned aerial vehicles (UAVs) to operate safely in the national airspace where non-collaborating flying objects, such as general aviation (GA) aircraft without automatic dependent surveillance-broadcast (ADS-B), exist, the UAVs' capability of “seeing" these objects is especially important. This “seeing", or sensing, can be implemented via various means, such as Radar or Lidar. Here we consider using cameras mounted on UAVs only, which has the advantage of light weight and low power. For the visual system to work well, it is required that the camera-based sensing capability should be at the level equal to or exceeding that of human pilots.
This thesis deals with two basic issues/challenges of the camera-based sensing of flying objects. The first one is the stabilization of the shaky videos taken on the UAVs due to vibrations at different locations where the cameras are mounted. In the thesis, we consider several algorithms, including Kalman filters and particle filters, for stabilization. We provide detailed theoretical discussions of these filters as well as their implementations. The second one is reliable detection and tracking of aircraft using image processing algorithms. We combine morphological processing and dynamic programming to accomplish good results under different situations. The performance evaluation of different image processing algorithms is accomplished using synthetic and recorded data.
Scholarly Commons Citation
Zhang, Yan, "Aircraft Detection and Tracking Using UAV-Mounted Vision System" (2015). PhD Dissertations and Master's Theses. 316.