Abstract

This paper focuses on linear Kalman Filter for Radar Target Tracking. Kalman filter uses recursive computations to attain a solution of discrete linear filter. Being an adaptive filter, Kalman filter analysis the relation between its estimated value and measured value, through a feedback loop and tries to attain the result after minimising the noises in the measured value. This research examines how measurement noise affects tracking performance of Radars in three dimensions in terms of relative prediction error at various SNR.