**Kaminer et al. 1999 :** Addresses the problem of navigation system design for autonomous
aircraft landing. New nonlinear filter structures are introduced to estimate
the position of an aircraft with respect to a possibly moving landing site,
such as a naval vessel, based on measurements provided by airborne vision and inertial sensors. By exploring the geometry of
the navigation problem, the navigation filter dynamics are cast in the
framework of linear parametrically varying systems (LPVs). Using this set-up,
filter performance and stability are studied in an H_{∞ }setting
by resorting to the theory of linear matrix inequalities (LMIs). The design of
nonlinear, globally stable filters to meet adequate H_{∞} performance
measures is thus converted into that of determining the feasibility of a
related set of LMIs and finding a solution to them, if it exists. This is done
by resorting to widely available numerical tools that borrow from convex
optimization techniques. The paper develops the mathematical framework that is
required for integrated vision/inertial navigation
system design and details a design example for an air vehicle
landing on an aircraft carrier.