The development of effective target tracking and collision avoidance algorithms is essential
to the success of unmanned aerial vehicle (UAV) missions. In a dynamic environment, path …

Unmanned aerial vehicles (UAVs) play an invaluable role in information collection and data
fusion. Because of their mobility and the complexity of deployed environments, constant …

Unmanned Air Vehicles (UAVs) have recently attracted considerable attention in the
research community. In this paper, we focus on their use in a simple target tracking …

Beginning with the derivation of a least squares estimator that yields an estimate of the
acceleration input vector, this paper first develops a detector for sensing target maneuvers …

A novel approach to position and orientation estimation for vision-based UAV (unmanned
aerial vehicle) navigation is described. In this approach the position and orientation …

Two Kalman filter based schemes are proposed for tracking maneuvering targets. Both
schemes use least squares to estimate a target's acceleration input vector and to update the …

A method for navigation of a small UAV through an unsurveyed environment (eg a forest) is
presented. In particular the problem of estimating the state of the aircraft and of obstacles in …

Safe, autonomous operation in complex, cluttered environments is a critical challenge facing
autonomous mobile systems. The research described in this paper was motivated by a …

The majority of tactical weapons systems require that manned maneuverable vehicles, such
as aircraft, ships, and submarines, be tracked accurately. An optimal Kalman filter has been …

The Kalman filter (KF) has been widely used in the state estimation of a target, but in the
presence of a manoeuvre, its performance may be seriously degraded because the …