Unmanned aircraft navigation for shipboard landing using infrared vision

This paper addresses the problem of determining the relative position and orientation of an unmanned air vehicle with respect to a ship using three visible points of known separation. The, images of the points are obtained from an onboard infrared camera. The paper develops a numerical solution to this problem. Both simulation and flight test results are presented.     

Linear parametrically varying systems with brief instabilities: an application to vision/inertial navigation

This paper addresses the problem of nonlinear filter design to estimate the relative position and velocity of an unmanned air vehicle (UAV) with respect to a point on a ship using infrared (IR) vision, inertial, and air data sensors. Sufficient conditions are derived for the existence of a particular type of complementary filters with guaranteed stability and performance in the presence of so-called out-of-frame events that arise when the vision system loses its target temporarily. The results obtained build upon new developments in the theory of linear parametrically varying systems (LPVs) with brief instabilities - also reported in the paper - and provide the proper framework to deal with out-of-frame events. Field tests with a prototype UAV illustrate the performance of the filter and the scope of applications of the new theory developed.     

Application of nonlinear filtering to navigation system designusing passive sensors

The problem of navigation system design for autonomous aircraft landing is addressed. New nonlinear filter structures are introduced to estimate the position and velocity 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, regionally 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 using-widely available numerical tools that borrow from convex optimization techniques. The mathematical framework that is required for integrated vision/inertial navigation system design is developed and a design example for an air vehicle landing on an aircraft carrier is detailed     

Online generation of quasi-optimal spacecraft rendezvous trajectories

A direct method for rapid generation of combined time-propellant near-optimal trajectories of proximity maneuvers of a chaser spacecraft required to dock a target one, with predetermined thrust history along a master direction, is presented. The predetermined thrust history is generated by applying the Pontryagin maximum principle. The new direct method, already implemented and tested on board real aircraft, is based on three concepts: high-order polynomials as reference functions, preset on–off sequence of a master control, and reduction of the optimization problem to the determination of a small set of parameters. Presetting the master control, the remaining controls act as slaves, guarantying the chaser to move along the desired path. Seeking of the optimum strategy is transformed into a nonlinear programming problem, and then numerically solved through an ad hoc algorithm in accelerated time scale. Examples are reported to prove the rapidness of the approach to generate a sub-optimal docking trajectory.