Application of the sliding innovation filter to unmanned aerial systems

Abstract

The applications of unmanned aerial systems (UASs) have grown in popularity due to their simplicity and availability. The quality of UAS's performance depends usually on adding several sensors and controllers that improve accuracy and flight performance. However, this typically increases the overall cost of the system. In this paper, a technique to enhance the performance while maintaining UAS affordability is proposed. This technique involves the use of an estimation strategy to extract hidden information from only a few sensors while improving the quality of the achieved signal. The simulation results of this method show strong performance, and are compared with another well-known estimation method.