Angular velocity estimation of fast spinning object using an imaging sensor

We propose a new spinning object angular velocity estimation method using an imaging sensor. Most of the previous algorithms require a knowledge of the attitude or of the body vector measurements. For a fast spinning object, however, the body vector measurement is a difficult task due to flows of the object image. To overcome this difficulty, we search for the angular velocity which minimizes the cost function defined by the Euclidean distance differences of the observed star traces and the derivative star traces of an estimated angular velocity. With this formulation, angular velocity determination becomes a kind of minimization problem in 3D of the angular velocity vector. To reduce the search dimensions and use search techniques in 1D, we randomly sample points on the star traces and these random points assign a constraint to the possible angular velocity vector according to the kinematics equation. A numerical simulation for fast spinning cases is carried out to establish the results.