Dead reckoning and terrain image processing as basis for UAV home-oriented navigation under foreign GPS-denied environments

Unmanned Aerial Vehicle (UAV) navigation within GPS-denied environments has become increasingly critical in recent years due to modern heavy reliance on GPS and the rise of UAV flight within GPS-denied and GPS-unstable zones. GPS reliance marks on the of the largest weaknesses of most autonomous UAV systems, and the loss of GPS signal often renders many autonomous UAVs completely coordinately-impaired. To confront this issue, this paper presents the implementation of a navigational system based upon dead reckoning and terrain imaging for home-oriented navigation, which is viable even in foreign environments. It explores the possibility of utilizing various forms of image processing, such as feature extraction and matching (SIFT) and optical flow via template matching, in order to replicate similar data that would have otherwise been produced by GPS outputs (namely, confirmation of an estimated final location with real location through image feature comparisons, ground speed calculations from terrain distance movement). This paper uses traditional dead reckoning methods as a path basis for the initial UAV navigation, and it applies both physical implementation and formal methods to study the viability of this solution.