An Improved Strong Tracking Kalman Filter Algorithm for the Initial Alignment of the Shearer
Joint Authors
Li, Wei
Xin, Gaifang
Chen, Yuming
Yang, Hai
Xia, Ting
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-18
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The strap-down inertial navigation system (SINS) is a commonly used sensor for autonomous underground navigation, which can be used for shearer positioning under a coal mine.
During the process of initial alignment, inaccurate or time-varying noise covariance matrices will significantly degrade the accuracy of the initial alignment of the shearer.
To overcome the performance degradation of the existing initial alignment algorithm under complex underground environment, a novel adaptive filtering algorithm is proposed by the integration of the strong tracking Kalman filter and the sequential filter for the initial alignment of the shearer with complex underground environment.
Compared with the traditional multiple fading factor strong tracking Kalman filter (MSTKF) method, the proposed MSTSKF algorithm integrates the advantage of strong tracking Kalman filter and sequential filter, and multiple fading factor and forgetting factor for east and north velocity measurement are designed in the algorithm, respectively, which can effectively weaken the coupling relationship between the different states and increase strong robustness against process uncertainties.
The simulation and experiment results show that the proposed MSTSKF method has better initial alignment accuracy and robustness than existing strong tracking Kalman filter algorithm.
American Psychological Association (APA)
Chen, Yuming& Li, Wei& Xin, Gaifang& Yang, Hai& Xia, Ting. 2019. An Improved Strong Tracking Kalman Filter Algorithm for the Initial Alignment of the Shearer. Complexity،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1131347
Modern Language Association (MLA)
Chen, Yuming…[et al.]. An Improved Strong Tracking Kalman Filter Algorithm for the Initial Alignment of the Shearer. Complexity No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1131347
American Medical Association (AMA)
Chen, Yuming& Li, Wei& Xin, Gaifang& Yang, Hai& Xia, Ting. An Improved Strong Tracking Kalman Filter Algorithm for the Initial Alignment of the Shearer. Complexity. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1131347
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1131347