Navigation for fixed-wing unmanned aerial vehicles in the presence of GNSS outages

The accuracy of the most commonly used integrated navigation system of inertial navigation system (INS) and global navigation satellite system (GNSS) is greatly influenced by the quality of satellite signals. Based on the most commonly used navigation system that is equipped with barometer and airspeedometer, a new navigation algorithm is proposed for fixed-wing unmanned aerial vehicles (UAVs) to bridge GNSS outages. We estimate the constant component of wind and subtract it from the airspeed to obtain the ground velocity in the presence of GNSS outages. Then, a centripetal force model is introduced to estimate the motion acceleration. Compensated by this acceleration, the gravity vector can be extracted from the accelerometer measurement. Finally, an extended Kalman filter (EKF) is used to integrate the reconstructed system. The presented algorithm is implemented and the hardware-in-loop simulation results illustrate that the new method significantly improves the accuracy for dynamic navigation relative to INS-only solutions during GNSS outages.