U—D分解的固定区间平滑新算法及其在飞行状态估计中的应用

A New U—D Factorization—based Fixed—interval Smoother and Application to Flight Test

中文关键词  固定区间平滑  状态估计  Kalman滤波  飞行试验

英文关键词  fixed—interval smoother  state estimation  kalman filter  flight test

中文摘要

      鉴于目前固定区间平滑算法所存在的问题，本文根据Rauch—Tung—Striebd平滑公式，提出了一种U—D分解形式的固定区间平滑新算法。这种方法既有良好的数值稳定性和可靠性，又具有计算量小的优点。它比Bierman序列方法和Keigo.Watanabe的前向平滑方法都有效得多。此外，本文对状态和偏差的同时平滑进行了讨论，并把它用于实际飞行状态的估计，所得结果较理想。

英文摘要

      In this paper, a new computationally efficient U—D factorization—based fixed—interval smoother is developed by using Rauch—Tung—Striebd smoother. This algorithm is of both numerical stable and computationally efficient since numerically superior modified weighted Gram—Schmidt method is used and computationally burdensome covariance matrix inversion does not involved. The results of the comparison of operation counts show that the method presented in this paper is much more efficient than Bierman rank 2 or Keigo. Watanabe forward —pass smoothing algorithm. Moreover, state and bias smoothing is discussed and this method has been applied to the determination of flight states and instruction errors.