GPS/INS integration in a S&A algorithm based on aircraft performances estimation

In this paper the fusion between the data derived from the Global Positioning System (GPS) and the Inertial navigation System (INS) is integrated in a Sense And Avoid (S&A) system for Unmanned Aerial Vehicle (UAV) to increase its performances. The avoidance manoeuvre is defined in order to provide a minimum separation between the ownship and all the other agents during its overall execution in multiple flying threats scenarios. This is achieved by aiding the GPS measurements with the INS to estimate the ownship position using an Extended Kalman Filter (EKF) which uses a linear error model to estimate the errors in the INS states. The resolution manoeuvre are defined as step variations in the heading angle and altitude commands of the Flight Path Control System (FPCS). The value of these commands is optimised in order to get the minimum step command value necessary to keep a minimum predefined separation between the ownship and all the threats.