An Intelligent Portable Aerial Surveillance System: Modeling and Image Stitching

Unmanned Aerial Vehicles (UAVs) have been widely used in modern warfare for surveillance, reconnaissance and even attack missions. They can provide valuable battlefield information and accomplish dangerous tasks with minimal risk of loss of lives and personal injuries. However, existing UAV systems are far from perfect to meet all possible situations. One of the most notable situations is the support for individual troops. Besides the incapability to always provide images in desired resolution, currently available systems are either too expensive for large-scale deployment or too heavy and complex for a single solder. Intelligent Portable Aerial Surveillance System (IPASS), sponsored by the Air Force Research Laboratory (AFRL), is aimed at developing a low-cost, light-weight unmanned aerial vehicle that can provide sufficient battlefield intelligence for individual troops. The main contributions of this thesis are two-fold (1) the development and verification of a model-based flight simulation for the aircraft, (2) comparison of image stitching techniques to provide a comprehensive aerial surveillance information from multiple vision. To assist with the design and control of the aircraft, dynamical models are established at different complexity levels. Simulations with these models are implemented in Matlab to study the dynamical characteristics of the aircraft. Aerial images acquired from the three onboard cameras are processed after getting the flying platform built. How a particular image is formed from a camera and the general pipeline of the feature-based image stitching method are first introduced in the thesis. To better satisfy the needs of this application, a homography-based stitching method is studied. This method can greatly reduce computation time with very little compromise in the quality of the panorama, which makes real-time video display of the surroundings on the ground station possible. By implementing both of the methods for image stitching using OpenCV, a quantitative comparison in the performance is accomplished