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<正>We consider the problem of initializing the tracking filter of a target moving with nearly constant velocity when position- only(1D,2D,or 3D)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.