The radar with high sampling rate always fails to track a slow moving target when using nearest neighbor data association under the clutter background, since its measuring error is much greater than the real moving distance of the target.To improve tracking precision to the slow moving target, an adaptive range nearest neighbor data association algorithm is proposed.This method uses the location information of the state vector to calculate the real range instead of calculating the statistical range of prediction center and measurements, the tracking precision is improved by reducing the missing association probability.The real range gate size relates to measuring error and the distance of radar and target.Simulation results show that the algorithm can enable the radar with high sampling rate track the low-moving target effectively with relatively high precision.