Time-Frequency Peak Filtering Versus Kalman Filter in the Kinematic Trajectory Estimation

The kinematic trajectory of point targets with timefrequency peak filtering and Kalman filtering has been used in this paper. The comparison of the named filters is done on position estimation of several characteristic generated trajectories. Firstly, the error estimation of a point target trajectory was analysed in one dimension and then in the plane. The criterion of a root mean square error is used to compare the estimation results of the used filters. It is shown that timefrequency peak filtering can be used in the trajectory estimation in various velocity values as well as in different variances of Gaussian noise.