|dc.description.abstract||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 is
implemented 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 singularity
could be solved by an alternative mechanization, the developmental nature of the
project inspire a singularity free implementation.
In this thesis a singularity-free navigation system for the LocalHawk UAV is
developed. 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 states
can be added and removed easily. The error state formulation allows the higher-rate
strapdown computer to work independently of the Kalman filter, and a navigation
solution can be computed when the aiding sensors are unable to provide measure-
ments. The attitude is represented by means of a direction cosine matrix, which
is a singularity free representation, and vector measurements are used for the atti-
tude. In addition, the added benefit from tightly coupled global navigation satellite
systems (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.||