Abstract: In this paper, a new information filter and fixed-interval smoother algorithms based on Kalman filter and Rauch-Tung-Striebel smoother are presented, and U-D factorization is used both in the new filter and smoother to get high computational efficiency. These new algorithms exhibit excellent numerical accuracy and stability and the number of operations of both the filter and smoother are decreased greatly since the structures of the new estimators are rearranged. Comparison of operation numbers shows that the new information filter and fixed-interval smoother is more than 1.7 times as fast as Bierman's sequential smoother and Keigo. Watanabe's forward-pass smoother.