  The introduction of automated flight control and management systems have made
possible aircraft designs that sacrifice arodynamic stability in order to
incorporate stealth technology intro their shape, operate more efficiently, and
are highly maneuverable. Therefore, modern flight management systems are
reliant on multiple redundant sensors to monitor and control the rotations of
the aircraft. To this end, a novel distributed quaternion Kalman filtering
algorithm is developed for tracking the rotation and orientation of an aircraft
in the three-dimensional space. The algorithm is developed to distribute
computation among the sensors in a manner that forces them to consent to a
unique solution while being robust to sensor and link failure, a desirable
characteristic for flight management systems. In addition, the underlying
quaternion-valued state space model allows to avoid problems associated with
gimbal lock. The performance of the developed algorithm is verified through
simulations.
