With the current diverse indoor and outdoor applications for drones in our daily life, there is a growing demand on the development of accurate self-monitoring systems to guarantee the safety of people and protect expensive assets. This project aims to improve the flight performance of the self-monitored drones using RF shadowing technology. RF shadowing has been adopted as a proven technology in several research areas for different applications, including localization, human health monitoring, agriculture applications, among others. Motivated by RF sensing advantages, we investigate the impact of fusing RF-based sensing with the other drone’s sensors on the motion performance. This fusion improves the early failure diagnoses and increases the drone’s performance in critical cases such as bad weather.