Implementation of Unscented Kalman Filter to Autonomous Aerial Vehicle for Target Tracking

Abstract

Unscented kalman filter is applied for tracking of a 3-dimensional autonomous aerial target. The noise corrupted measurements are smoothed and at the same time the vehicle's velocity components are found out. Detailed study is carried out in Monte-Carlo simulation. The outputs of the algorithm are compare with that of extended Kalman filter and are useful for releasing weapon on to the target.