Precise UAV Flight Management Based on Sensor Fusion with Integrity Monitoring

The use of commercial Unmanned Aerial Vehicles (UAVs) has boomed in recent years. This increasing use has brought with significant challenges in respect to UAV flight management, however. As one of the liability-critical applications, UAV flight management requires precise knowledge of the real-time vehicle state in flight, as well as timely alerts to relevant users or entities before a risky event happens, such as intrusion into a no-fly zone. This paper, therefore, presents the user level, accuracy and integrity requirements for unmanned aerial vehicle flight management. We go on then to design a sensor fusion based positioning system to meet the aforementioned requirements. This uses a Kalman filter to integrate Global Positioning System (GPS) data with Inertial Navigation System (INS) data, based on the pseudorange measurements. In addition, an integrity monitoring algorithm is proposed based on a dual-mode fault detector and w test statistics, and real-time dynamic horizontal protection level computation. Onboard experimental results show that the proposed algorithm is capable of delivering the accuracy and integrity requirements for precise UAV flight management.