The object of this paper is to introduce a new method for computing the linear velocity and angular velocity of an unmanned air vehicle (UAV) using only the information obtained from image sequences. In UAV applications, computational resources are limited due to payload constraints and the real-time computation requirement. Therefore, computationally intensive techniques employing feature extraction cannot be used. The alternative, in existing literature, is the computation of optical flow and

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... the subsequent computation of motion. Both of these problems are ill-posed due to the correspondence and aperture problems. In this paper, we consider a different approach for motion estimation that is based on the spatial differentiation of an image function. We show that the solution is a well-posed problem that involves a least squares problem and nonlinear filtering. We also discuss the implementation of such a scheme on a UAV, and discuss the existence of such schemes in insects and crustaceans. R. Iyer and R. Holsapple are with the Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409 USA. P. Chandler is with the U.S. Air Force Research Laboratory, Wright-Patterson Air Force Base, Ohio 45433-7531.