Adaptive Robust Least-Squares Smoothing Algorithm

Xu Lin

doi:10.1109/TIM.2022.3210970

2022-01-01

PRE

DOI：10.1109/TIM.2022.3210970

原文链接

原文求助

摘要

En 中文

The Kalman smoothing algorithm is widely used in offline data processing in global navigation satellites system (GNSS) to improve filter calculation accuracy. When there are measurement outliers or biased random models, the adaptive Kalman smoothing algorithm can reduce their impact on the smoothing results to a certain extent. Nevertheless, the adaptive Kalman smoothing algorithm usually has difficulty obtaining optimal estimation in a complex observation environment due to the inherent defects of the algorithm itself. Therefore, we propose an adaptive robust least-squares smoothing algorithm. The row and column transformation of the least-square smooth noise covariance matrix is realized by constructing an orthogonal space transformation matrix, and the noise covariance estimation problem of the Kalman filter is transformed into the problem of solving the variance-covariance component elements under a specific matrix structure. In addition, by selecting the observation value with the largest standardized residual to determine whether it is a gross error, we avoid the gross error misjudgment problem caused by the two-factor robust estimation method under least-square smoothing and further improve the smoothing accuracy. Finally, two experiments are studied to compare the performance of the new algorithm and the state-of-the-art algorithms. The proposed algorithm has demonstrated better performance in terms of robustness and estimation accuracy.

Keyword:

Smoothing methods

Estimation

Kalman filters

Mathematical models

Noise measurement

State estimation

Resists

Least squares

noise covariance estimation

robust estimation

smoothing

期刊

IEEE Transactions on Instrumentation and Measurement

IF:

5.9

论文数:

2.0W

被引数:

5.8W

机构

Chengdu University of Technology

学者数:

1.2W

论文数: 6.9K

被引数: 24

引用论文

Research on Remaining Useful Life Prediction of Rolling Element Bearings Based on Time-Varying Kalman Filter

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

IF5.9

2020-06-01

167

PREAI

Cui, Lingli; Wang, Xin; Wang, Huaqing; Ma, Jianfeng

660 Chronotype Associations with Insomnia, Depressive Symptoms, and Changes in Sleep and Health Behaviors during the COVID-19 Pandemic

Sleep

IF0

2021-05-03

OAAI

Megan Petrov; Matthew Buman; Dana Epstein; Shawn Youngstedt; Nicole Hoffmann; Jennifer Mattingly; Kristina Hasanaj; Nana Jiao; Kimiya Kasraeian; Anthony Sominsky; Elena Stievater

Effects of ABCDE Bundle Implementation on Reduction of Delirium among Mechanically Ventilated Patients at Damietta Hospital, Egypt

Open Journal of Nursing and Medical Care

IF0

2021-02-22