Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
694680 | Acta Automatica Sinica | 2008 | 8 Pages |
We consider the problem of initializing the tracking filter of a target moving with nearly constant velocity when position- only (1D,2D,or3D) measurements are available. It is known that the Kalman filter is optimal for such a problem, provided it is correctly initialized. We compare a single-point and the well-known two-point difference track initialization algorithms. We analytically show that if the process noise approaches zero and the maximum speed of a target used to initialize the velocity variance approaches infinity, then the single-point algorithm reduces to the two-point difference algorithm. We present numerical results that show that the single-point algorithm performs consistently better than the two-point difference algorithm in the mean square error sense. We also present analytical results that support the conjecture that this is true in general.