Singularity-Free Navigation System for an Autonomous Unmanned Aerial Vehicle
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For unmanned aerial vehicles (UAVs) to take off and land on limited areas ver-tical take-off and landing capabilities can be greatly beneficial. Such a system isimplemented in Kongsberg s LocalHawk project.A key challenge in vertical landing is vertical position and velocity estimation.Some airframe designs take-off and land with a 90 degree pitch. While the singularitycould be solved by an alternative mechanization, the developmental nature of theproject inspire a singularity free implementation.In this thesis a singularity-free navigation system for the LocalHawk UAV isdeveloped. This is done in the framework of the error-state formulation of the ex-tended Kalman filter, which allows for a modular system where sensors and statescan be added and removed easily. The error state formulation allows the higher-ratestrapdown computer to work independently of the Kalman filter, and a navigationsolution can be computed when the aiding sensors are unable to provide measure-ments. The attitude is represented by means of a direction cosine matrix, whichis a singularity free representation, and vector measurements are used for the atti-tude. In addition, the added benefit from tightly coupled global navigation satellitesystems (GNSS) improve the solution during periods of reduced signal coverage,particularly during maneuvers.Simulations indicate that it may be possible to land vertically with onboard sen-sors. Landing without aiding sensors caused too large uncertainty in the estimates,and should not be attempted.